{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- Size: Long lowest siza firms,and short highest size firms\n",
    "- Value: Long highest value stocks,and short lowest value firms\n",
    " - EP: earnings to price ratio 相对于公司赚钱能力，公司股价是什么水平\n",
    " - Value stock 价值股 Growth stock 成长股"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import scipy.stats as stats #统计模块\n",
    "import scipy\n",
    "# import pymysql #导入数据库模块\n",
    "\n",
    "from datetime import datetime #时间模块\n",
    "import statsmodels.formula.api as smf # OLS regression\n",
    "\n",
    "# import pyreadr # read RDS file\n",
    "\n",
    "from matplotlib import style\n",
    "import matplotlib.pyplot as plt #画图模块\n",
    "import matplotlib.dates as mdates\n",
    "\n",
    "from matplotlib.font_manager import FontProperties #作图中文\n",
    "from pylab import mpl\n",
    "\n",
    "# 输出矢量图 渲染矢量图\n",
    "%matplotlib inline\n",
    "%config InlineBackend.figure_format='svg'\n",
    "\n",
    "from IPython.core.interactiveshell import InteractiveShell #jupyter运行输出的模块\n",
    "#显示每一个运行结果\n",
    "InteractiveShell.ast_node_interactivity='all'\n",
    "\n",
    "#设置列不限制数量\n",
    "pd.set_option('display.max_columns',None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Stkcd</th>\n",
       "      <th>month</th>\n",
       "      <th>price</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Freq</th>\n",
       "      <th>floatingvalue</th>\n",
       "      <th>totalvalue</th>\n",
       "      <th>sizef</th>\n",
       "      <th>sizet</th>\n",
       "      <th>Return</th>\n",
       "      <th>rfmonth</th>\n",
       "      <th>ret</th>\n",
       "      <th>next_ret</th>\n",
       "      <th>w</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-05-31</td>\n",
       "      <td>38.34</td>\n",
       "      <td>2</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.016010e+09</td>\n",
       "      <td>1.859497e+09</td>\n",
       "      <td>20.739149</td>\n",
       "      <td>21.343572</td>\n",
       "      <td>-0.122253</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.128345</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-06-30</td>\n",
       "      <td>33.99</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>9.007350e+08</td>\n",
       "      <td>1.648521e+09</td>\n",
       "      <td>20.618722</td>\n",
       "      <td>21.223144</td>\n",
       "      <td>-0.113459</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-07-31</td>\n",
       "      <td>29.54</td>\n",
       "      <td>4</td>\n",
       "      <td>16.0</td>\n",
       "      <td>7.828100e+08</td>\n",
       "      <td>1.432695e+09</td>\n",
       "      <td>20.478401</td>\n",
       "      <td>21.082823</td>\n",
       "      <td>-0.130921</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-08-31</td>\n",
       "      <td>15.00</td>\n",
       "      <td>5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.748338e+08</td>\n",
       "      <td>1.346275e+09</td>\n",
       "      <td>20.329977</td>\n",
       "      <td>21.020607</td>\n",
       "      <td>-0.411588</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-09-30</td>\n",
       "      <td>14.50</td>\n",
       "      <td>6</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.523394e+08</td>\n",
       "      <td>1.301399e+09</td>\n",
       "      <td>20.296075</td>\n",
       "      <td>20.986706</td>\n",
       "      <td>-0.033333</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>0.849080</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752023</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>13.56</td>\n",
       "      <td>24</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.955351e+09</td>\n",
       "      <td>1.054667e+10</td>\n",
       "      <td>22.797111</td>\n",
       "      <td>23.079076</td>\n",
       "      <td>-0.025862</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752024</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>14.54</td>\n",
       "      <td>25</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.530295e+09</td>\n",
       "      <td>1.130889e+10</td>\n",
       "      <td>22.866890</td>\n",
       "      <td>23.148855</td>\n",
       "      <td>0.072271</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752025</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>13.85</td>\n",
       "      <td>26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.125488e+09</td>\n",
       "      <td>1.077222e+10</td>\n",
       "      <td>22.818272</td>\n",
       "      <td>23.100237</td>\n",
       "      <td>-0.047455</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752026</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>13.48</td>\n",
       "      <td>27</td>\n",
       "      <td>22.0</td>\n",
       "      <td>7.908417e+09</td>\n",
       "      <td>1.048444e+10</td>\n",
       "      <td>22.791193</td>\n",
       "      <td>23.073159</td>\n",
       "      <td>-0.026715</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752027</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>14.89</td>\n",
       "      <td>28</td>\n",
       "      <td>21.0</td>\n",
       "      <td>8.735632e+09</td>\n",
       "      <td>1.158111e+10</td>\n",
       "      <td>22.890676</td>\n",
       "      <td>23.172641</td>\n",
       "      <td>0.104599</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>709883 rows × 14 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Stkcd      month  price  Rank  Freq  floatingvalue    totalvalue  \\\n",
       "1       000001 1991-05-31  38.34     2  24.0   1.016010e+09  1.859497e+09   \n",
       "2       000001 1991-06-30  33.99     3  23.0   9.007350e+08  1.648521e+09   \n",
       "3       000001 1991-07-31  29.54     4  16.0   7.828100e+08  1.432695e+09   \n",
       "4       000001 1991-08-31  15.00     5  15.0   6.748338e+08  1.346275e+09   \n",
       "5       000001 1991-09-30  14.50     6  24.0   6.523394e+08  1.301399e+09   \n",
       "...        ...        ...    ...   ...   ...            ...           ...   \n",
       "752023  605599 2023-08-31  13.56    24  23.0   7.955351e+09  1.054667e+10   \n",
       "752024  605599 2023-09-30  14.54    25  20.0   8.530295e+09  1.130889e+10   \n",
       "752025  605599 2023-10-31  13.85    26  17.0   8.125488e+09  1.077222e+10   \n",
       "752026  605599 2023-11-30  13.48    27  22.0   7.908417e+09  1.048444e+10   \n",
       "752027  605599 2023-12-31  14.89    28  21.0   8.735632e+09  1.158111e+10   \n",
       "\n",
       "            sizef      sizet    Return   rfmonth       ret  next_ret  w  \n",
       "1       20.739149  21.343572 -0.122253  0.006092 -0.128345 -0.119551  1  \n",
       "2       20.618722  21.223144 -0.113459  0.006092 -0.119551 -0.137013  1  \n",
       "3       20.478401  21.082823 -0.130921  0.006092 -0.137013 -0.417680  1  \n",
       "4       20.329977  21.020607 -0.411588  0.006092 -0.417680 -0.039425  1  \n",
       "5       20.296075  20.986706 -0.033333  0.006092 -0.039425  0.849080  1  \n",
       "...           ...        ...       ...       ...       ...       ... ..  \n",
       "752023  22.797111  23.079076 -0.025862  0.001241 -0.027103  0.071030  1  \n",
       "752024  22.866890  23.148855  0.072271  0.001241  0.071030 -0.048696  1  \n",
       "752025  22.818272  23.100237 -0.047455  0.001241 -0.048696 -0.027956  1  \n",
       "752026  22.791193  23.073159 -0.026715  0.001241 -0.027956  0.103358  1  \n",
       "752027  22.890676  23.172641  0.104599  0.001241  0.103358       NaN  1  \n",
       "\n",
       "[709883 rows x 14 columns]"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cross = pd.read_csv(\"D:/python-homework/python-homework/ret_mon_python2023.csv\")\n",
    "from pandas.tseries.offsets import MonthEnd\n",
    "cross['month'] = pd.to_datetime(cross['month'], format='%Y-%m-%d') + MonthEnd(1)\n",
    "# 补齐股票代码 如果不满6位 在前面补上0\n",
    "cross['Stkcd'] = cross['Stkcd'].apply(lambda x: '{:0>6}'.format(x)) # 6位股票代码\n",
    "cross['w'] = 1\n",
    "cross = cross.dropna(subset=['ret'])#丢掉了收益率缺失的数据\n",
    "cross"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "      <th>four</th>\n",
       "      <th>five</th>\n",
       "      <th>six</th>\n",
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       "      <th>eight</th>\n",
       "      <th>nine</th>\n",
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       "      <th>month</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1991-01-31</th>\n",
       "      <td>7.499850e+06</td>\n",
       "      <td>1.324290e+07</td>\n",
       "      <td>4.841034e+07</td>\n",
       "      <td>8.357778e+07</td>\n",
       "      <td>1.645389e+08</td>\n",
       "      <td>2.455000e+08</td>\n",
       "      <td>5.287392e+08</td>\n",
       "      <td>8.119784e+08</td>\n",
       "      <td>9.109892e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-02-28</th>\n",
       "      <td>1.168762e+07</td>\n",
       "      <td>1.787684e+07</td>\n",
       "      <td>6.941160e+07</td>\n",
       "      <td>1.426559e+08</td>\n",
       "      <td>2.168625e+08</td>\n",
       "      <td>4.029251e+08</td>\n",
       "      <td>6.804663e+08</td>\n",
       "      <td>8.582599e+08</td>\n",
       "      <td>1.065150e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-03-31</th>\n",
       "      <td>1.098601e+07</td>\n",
       "      <td>1.691778e+07</td>\n",
       "      <td>4.002500e+07</td>\n",
       "      <td>7.086472e+07</td>\n",
       "      <td>1.199623e+08</td>\n",
       "      <td>3.103026e+08</td>\n",
       "      <td>6.328671e+08</td>\n",
       "      <td>8.540667e+08</td>\n",
       "      <td>9.379800e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-04-30</th>\n",
       "      <td>1.106975e+07</td>\n",
       "      <td>1.805230e+07</td>\n",
       "      <td>3.729500e+07</td>\n",
       "      <td>6.259785e+07</td>\n",
       "      <td>1.070732e+08</td>\n",
       "      <td>2.760596e+08</td>\n",
       "      <td>5.889068e+08</td>\n",
       "      <td>8.629674e+08</td>\n",
       "      <td>9.611433e+08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-05-31</th>\n",
       "      <td>1.310760e+07</td>\n",
       "      <td>2.075000e+07</td>\n",
       "      <td>3.930000e+07</td>\n",
       "      <td>7.435439e+07</td>\n",
       "      <td>1.237500e+08</td>\n",
       "      <td>4.656752e+08</td>\n",
       "      <td>8.200000e+08</td>\n",
       "      <td>9.495000e+08</td>\n",
       "      <td>1.179490e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>2.409184e+09</td>\n",
       "      <td>2.989534e+09</td>\n",
       "      <td>3.635605e+09</td>\n",
       "      <td>4.424176e+09</td>\n",
       "      <td>5.520202e+09</td>\n",
       "      <td>7.084067e+09</td>\n",
       "      <td>9.755098e+09</td>\n",
       "      <td>1.501682e+10</td>\n",
       "      <td>2.876172e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>2.421632e+09</td>\n",
       "      <td>2.985093e+09</td>\n",
       "      <td>3.638369e+09</td>\n",
       "      <td>4.403628e+09</td>\n",
       "      <td>5.487673e+09</td>\n",
       "      <td>7.058126e+09</td>\n",
       "      <td>9.799861e+09</td>\n",
       "      <td>1.484667e+10</td>\n",
       "      <td>2.831428e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>2.409577e+09</td>\n",
       "      <td>2.957719e+09</td>\n",
       "      <td>3.627091e+09</td>\n",
       "      <td>4.384522e+09</td>\n",
       "      <td>5.401911e+09</td>\n",
       "      <td>6.984732e+09</td>\n",
       "      <td>9.608270e+09</td>\n",
       "      <td>1.451708e+10</td>\n",
       "      <td>2.725788e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>2.539108e+09</td>\n",
       "      <td>3.126053e+09</td>\n",
       "      <td>3.791893e+09</td>\n",
       "      <td>4.588888e+09</td>\n",
       "      <td>5.702116e+09</td>\n",
       "      <td>7.194539e+09</td>\n",
       "      <td>9.833215e+09</td>\n",
       "      <td>1.482454e+10</td>\n",
       "      <td>2.753897e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>2.478696e+09</td>\n",
       "      <td>3.076500e+09</td>\n",
       "      <td>3.703741e+09</td>\n",
       "      <td>4.496844e+09</td>\n",
       "      <td>5.579697e+09</td>\n",
       "      <td>6.945948e+09</td>\n",
       "      <td>9.630063e+09</td>\n",
       "      <td>1.432934e+10</td>\n",
       "      <td>2.676280e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>396 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     one           two         three          four  \\\n",
       "month                                                                \n",
       "1991-01-31  7.499850e+06  1.324290e+07  4.841034e+07  8.357778e+07   \n",
       "1991-02-28  1.168762e+07  1.787684e+07  6.941160e+07  1.426559e+08   \n",
       "1991-03-31  1.098601e+07  1.691778e+07  4.002500e+07  7.086472e+07   \n",
       "1991-04-30  1.106975e+07  1.805230e+07  3.729500e+07  6.259785e+07   \n",
       "1991-05-31  1.310760e+07  2.075000e+07  3.930000e+07  7.435439e+07   \n",
       "...                  ...           ...           ...           ...   \n",
       "2023-08-31  2.409184e+09  2.989534e+09  3.635605e+09  4.424176e+09   \n",
       "2023-09-30  2.421632e+09  2.985093e+09  3.638369e+09  4.403628e+09   \n",
       "2023-10-31  2.409577e+09  2.957719e+09  3.627091e+09  4.384522e+09   \n",
       "2023-11-30  2.539108e+09  3.126053e+09  3.791893e+09  4.588888e+09   \n",
       "2023-12-31  2.478696e+09  3.076500e+09  3.703741e+09  4.496844e+09   \n",
       "\n",
       "                    five           six         seven         eight  \\\n",
       "month                                                                \n",
       "1991-01-31  1.645389e+08  2.455000e+08  5.287392e+08  8.119784e+08   \n",
       "1991-02-28  2.168625e+08  4.029251e+08  6.804663e+08  8.582599e+08   \n",
       "1991-03-31  1.199623e+08  3.103026e+08  6.328671e+08  8.540667e+08   \n",
       "1991-04-30  1.070732e+08  2.760596e+08  5.889068e+08  8.629674e+08   \n",
       "1991-05-31  1.237500e+08  4.656752e+08  8.200000e+08  9.495000e+08   \n",
       "...                  ...           ...           ...           ...   \n",
       "2023-08-31  5.520202e+09  7.084067e+09  9.755098e+09  1.501682e+10   \n",
       "2023-09-30  5.487673e+09  7.058126e+09  9.799861e+09  1.484667e+10   \n",
       "2023-10-31  5.401911e+09  6.984732e+09  9.608270e+09  1.451708e+10   \n",
       "2023-11-30  5.702116e+09  7.194539e+09  9.833215e+09  1.482454e+10   \n",
       "2023-12-31  5.579697e+09  6.945948e+09  9.630063e+09  1.432934e+10   \n",
       "\n",
       "                    nine  \n",
       "month                     \n",
       "1991-01-31  9.109892e+08  \n",
       "1991-02-28  1.065150e+09  \n",
       "1991-03-31  9.379800e+08  \n",
       "1991-04-30  9.611433e+08  \n",
       "1991-05-31  1.179490e+09  \n",
       "...                  ...  \n",
       "2023-08-31  2.876172e+10  \n",
       "2023-09-30  2.831428e+10  \n",
       "2023-10-31  2.725788e+10  \n",
       "2023-11-30  2.753897e+10  \n",
       "2023-12-31  2.676280e+10  \n",
       "\n",
       "[396 rows x 9 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#按照公司规模分组\n",
    "fenweishu = pd.DataFrame(\n",
    "    cross.groupby(['month'])['totalvalue'].quantile([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]))#分10组\n",
    "fenweishu = fenweishu.reset_index()#把索引去掉\n",
    "fenweishu = fenweishu.pivot_table(index='month',columns='level_1',values='totalvalue')#pivot的作用是数据变形，数据长变宽\n",
    "fenweishu.columns = ['one','two','three','four','five','six','seven','eight','nine']#改名\n",
    "fenweishu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Stkcd</th>\n",
       "      <th>month</th>\n",
       "      <th>price</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Freq</th>\n",
       "      <th>floatingvalue</th>\n",
       "      <th>totalvalue</th>\n",
       "      <th>sizef</th>\n",
       "      <th>sizet</th>\n",
       "      <th>Return</th>\n",
       "      <th>rfmonth</th>\n",
       "      <th>ret</th>\n",
       "      <th>next_ret</th>\n",
       "      <th>w</th>\n",
       "      <th>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "      <th>four</th>\n",
       "      <th>five</th>\n",
       "      <th>six</th>\n",
       "      <th>seven</th>\n",
       "      <th>eight</th>\n",
       "      <th>nine</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-05-31</td>\n",
       "      <td>38.34</td>\n",
       "      <td>2</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.016010e+09</td>\n",
       "      <td>1.859497e+09</td>\n",
       "      <td>20.739149</td>\n",
       "      <td>21.343572</td>\n",
       "      <td>-0.122253</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.128345</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>1</td>\n",
       "      <td>1.310760e+07</td>\n",
       "      <td>2.075000e+07</td>\n",
       "      <td>3.930000e+07</td>\n",
       "      <td>7.435439e+07</td>\n",
       "      <td>1.237500e+08</td>\n",
       "      <td>4.656752e+08</td>\n",
       "      <td>8.200000e+08</td>\n",
       "      <td>9.495000e+08</td>\n",
       "      <td>1.179490e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-06-30</td>\n",
       "      <td>33.99</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>9.007350e+08</td>\n",
       "      <td>1.648521e+09</td>\n",
       "      <td>20.618722</td>\n",
       "      <td>21.223144</td>\n",
       "      <td>-0.113459</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>1</td>\n",
       "      <td>1.568160e+07</td>\n",
       "      <td>2.530000e+07</td>\n",
       "      <td>4.680000e+07</td>\n",
       "      <td>6.750000e+07</td>\n",
       "      <td>8.803190e+07</td>\n",
       "      <td>5.041568e+08</td>\n",
       "      <td>8.460000e+08</td>\n",
       "      <td>9.808000e+08</td>\n",
       "      <td>1.424909e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-07-31</td>\n",
       "      <td>29.54</td>\n",
       "      <td>4</td>\n",
       "      <td>16.0</td>\n",
       "      <td>7.828100e+08</td>\n",
       "      <td>1.432695e+09</td>\n",
       "      <td>20.478401</td>\n",
       "      <td>21.082823</td>\n",
       "      <td>-0.130921</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>1</td>\n",
       "      <td>1.853584e+07</td>\n",
       "      <td>3.524000e+07</td>\n",
       "      <td>4.962750e+07</td>\n",
       "      <td>7.375645e+07</td>\n",
       "      <td>2.909111e+08</td>\n",
       "      <td>6.515875e+08</td>\n",
       "      <td>7.824435e+08</td>\n",
       "      <td>9.234410e+08</td>\n",
       "      <td>1.385166e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-08-31</td>\n",
       "      <td>15.00</td>\n",
       "      <td>5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.748338e+08</td>\n",
       "      <td>1.346275e+09</td>\n",
       "      <td>20.329977</td>\n",
       "      <td>21.020607</td>\n",
       "      <td>-0.411588</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>1</td>\n",
       "      <td>3.987000e+07</td>\n",
       "      <td>4.686000e+07</td>\n",
       "      <td>5.697000e+07</td>\n",
       "      <td>1.202482e+08</td>\n",
       "      <td>2.114458e+08</td>\n",
       "      <td>5.175314e+08</td>\n",
       "      <td>7.128432e+08</td>\n",
       "      <td>1.038883e+09</td>\n",
       "      <td>1.315300e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-09-30</td>\n",
       "      <td>14.50</td>\n",
       "      <td>6</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.523394e+08</td>\n",
       "      <td>1.301399e+09</td>\n",
       "      <td>20.296075</td>\n",
       "      <td>20.986706</td>\n",
       "      <td>-0.033333</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>0.849080</td>\n",
       "      <td>1</td>\n",
       "      <td>4.695500e+07</td>\n",
       "      <td>5.084500e+07</td>\n",
       "      <td>5.776000e+07</td>\n",
       "      <td>1.127927e+08</td>\n",
       "      <td>2.007668e+08</td>\n",
       "      <td>4.029891e+08</td>\n",
       "      <td>6.602826e+08</td>\n",
       "      <td>1.001743e+09</td>\n",
       "      <td>1.268519e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709878</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>13.56</td>\n",
       "      <td>24</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.955351e+09</td>\n",
       "      <td>1.054667e+10</td>\n",
       "      <td>22.797111</td>\n",
       "      <td>23.079076</td>\n",
       "      <td>-0.025862</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>1</td>\n",
       "      <td>2.409184e+09</td>\n",
       "      <td>2.989534e+09</td>\n",
       "      <td>3.635605e+09</td>\n",
       "      <td>4.424176e+09</td>\n",
       "      <td>5.520202e+09</td>\n",
       "      <td>7.084067e+09</td>\n",
       "      <td>9.755098e+09</td>\n",
       "      <td>1.501682e+10</td>\n",
       "      <td>2.876172e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709879</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>14.54</td>\n",
       "      <td>25</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.530295e+09</td>\n",
       "      <td>1.130889e+10</td>\n",
       "      <td>22.866890</td>\n",
       "      <td>23.148855</td>\n",
       "      <td>0.072271</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>1</td>\n",
       "      <td>2.421632e+09</td>\n",
       "      <td>2.985093e+09</td>\n",
       "      <td>3.638369e+09</td>\n",
       "      <td>4.403628e+09</td>\n",
       "      <td>5.487673e+09</td>\n",
       "      <td>7.058126e+09</td>\n",
       "      <td>9.799861e+09</td>\n",
       "      <td>1.484667e+10</td>\n",
       "      <td>2.831428e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709880</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>13.85</td>\n",
       "      <td>26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.125488e+09</td>\n",
       "      <td>1.077222e+10</td>\n",
       "      <td>22.818272</td>\n",
       "      <td>23.100237</td>\n",
       "      <td>-0.047455</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>1</td>\n",
       "      <td>2.409577e+09</td>\n",
       "      <td>2.957719e+09</td>\n",
       "      <td>3.627091e+09</td>\n",
       "      <td>4.384522e+09</td>\n",
       "      <td>5.401911e+09</td>\n",
       "      <td>6.984732e+09</td>\n",
       "      <td>9.608270e+09</td>\n",
       "      <td>1.451708e+10</td>\n",
       "      <td>2.725788e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709881</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>13.48</td>\n",
       "      <td>27</td>\n",
       "      <td>22.0</td>\n",
       "      <td>7.908417e+09</td>\n",
       "      <td>1.048444e+10</td>\n",
       "      <td>22.791193</td>\n",
       "      <td>23.073159</td>\n",
       "      <td>-0.026715</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>1</td>\n",
       "      <td>2.539108e+09</td>\n",
       "      <td>3.126053e+09</td>\n",
       "      <td>3.791893e+09</td>\n",
       "      <td>4.588888e+09</td>\n",
       "      <td>5.702116e+09</td>\n",
       "      <td>7.194539e+09</td>\n",
       "      <td>9.833215e+09</td>\n",
       "      <td>1.482454e+10</td>\n",
       "      <td>2.753897e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709882</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>14.89</td>\n",
       "      <td>28</td>\n",
       "      <td>21.0</td>\n",
       "      <td>8.735632e+09</td>\n",
       "      <td>1.158111e+10</td>\n",
       "      <td>22.890676</td>\n",
       "      <td>23.172641</td>\n",
       "      <td>0.104599</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>2.478696e+09</td>\n",
       "      <td>3.076500e+09</td>\n",
       "      <td>3.703741e+09</td>\n",
       "      <td>4.496844e+09</td>\n",
       "      <td>5.579697e+09</td>\n",
       "      <td>6.945948e+09</td>\n",
       "      <td>9.630063e+09</td>\n",
       "      <td>1.432934e+10</td>\n",
       "      <td>2.676280e+10</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>709883 rows × 23 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Stkcd      month  price  Rank  Freq  floatingvalue    totalvalue  \\\n",
       "0       000001 1991-05-31  38.34     2  24.0   1.016010e+09  1.859497e+09   \n",
       "1       000001 1991-06-30  33.99     3  23.0   9.007350e+08  1.648521e+09   \n",
       "2       000001 1991-07-31  29.54     4  16.0   7.828100e+08  1.432695e+09   \n",
       "3       000001 1991-08-31  15.00     5  15.0   6.748338e+08  1.346275e+09   \n",
       "4       000001 1991-09-30  14.50     6  24.0   6.523394e+08  1.301399e+09   \n",
       "...        ...        ...    ...   ...   ...            ...           ...   \n",
       "709878  605599 2023-08-31  13.56    24  23.0   7.955351e+09  1.054667e+10   \n",
       "709879  605599 2023-09-30  14.54    25  20.0   8.530295e+09  1.130889e+10   \n",
       "709880  605599 2023-10-31  13.85    26  17.0   8.125488e+09  1.077222e+10   \n",
       "709881  605599 2023-11-30  13.48    27  22.0   7.908417e+09  1.048444e+10   \n",
       "709882  605599 2023-12-31  14.89    28  21.0   8.735632e+09  1.158111e+10   \n",
       "\n",
       "            sizef      sizet    Return   rfmonth       ret  next_ret  w  \\\n",
       "0       20.739149  21.343572 -0.122253  0.006092 -0.128345 -0.119551  1   \n",
       "1       20.618722  21.223144 -0.113459  0.006092 -0.119551 -0.137013  1   \n",
       "2       20.478401  21.082823 -0.130921  0.006092 -0.137013 -0.417680  1   \n",
       "3       20.329977  21.020607 -0.411588  0.006092 -0.417680 -0.039425  1   \n",
       "4       20.296075  20.986706 -0.033333  0.006092 -0.039425  0.849080  1   \n",
       "...           ...        ...       ...       ...       ...       ... ..   \n",
       "709878  22.797111  23.079076 -0.025862  0.001241 -0.027103  0.071030  1   \n",
       "709879  22.866890  23.148855  0.072271  0.001241  0.071030 -0.048696  1   \n",
       "709880  22.818272  23.100237 -0.047455  0.001241 -0.048696 -0.027956  1   \n",
       "709881  22.791193  23.073159 -0.026715  0.001241 -0.027956  0.103358  1   \n",
       "709882  22.890676  23.172641  0.104599  0.001241  0.103358       NaN  1   \n",
       "\n",
       "                 one           two         three          four          five  \\\n",
       "0       1.310760e+07  2.075000e+07  3.930000e+07  7.435439e+07  1.237500e+08   \n",
       "1       1.568160e+07  2.530000e+07  4.680000e+07  6.750000e+07  8.803190e+07   \n",
       "2       1.853584e+07  3.524000e+07  4.962750e+07  7.375645e+07  2.909111e+08   \n",
       "3       3.987000e+07  4.686000e+07  5.697000e+07  1.202482e+08  2.114458e+08   \n",
       "4       4.695500e+07  5.084500e+07  5.776000e+07  1.127927e+08  2.007668e+08   \n",
       "...              ...           ...           ...           ...           ...   \n",
       "709878  2.409184e+09  2.989534e+09  3.635605e+09  4.424176e+09  5.520202e+09   \n",
       "709879  2.421632e+09  2.985093e+09  3.638369e+09  4.403628e+09  5.487673e+09   \n",
       "709880  2.409577e+09  2.957719e+09  3.627091e+09  4.384522e+09  5.401911e+09   \n",
       "709881  2.539108e+09  3.126053e+09  3.791893e+09  4.588888e+09  5.702116e+09   \n",
       "709882  2.478696e+09  3.076500e+09  3.703741e+09  4.496844e+09  5.579697e+09   \n",
       "\n",
       "                 six         seven         eight          nine  \n",
       "0       4.656752e+08  8.200000e+08  9.495000e+08  1.179490e+09  \n",
       "1       5.041568e+08  8.460000e+08  9.808000e+08  1.424909e+09  \n",
       "2       6.515875e+08  7.824435e+08  9.234410e+08  1.385166e+09  \n",
       "3       5.175314e+08  7.128432e+08  1.038883e+09  1.315300e+09  \n",
       "4       4.029891e+08  6.602826e+08  1.001743e+09  1.268519e+09  \n",
       "...              ...           ...           ...           ...  \n",
       "709878  7.084067e+09  9.755098e+09  1.501682e+10  2.876172e+10  \n",
       "709879  7.058126e+09  9.799861e+09  1.484667e+10  2.831428e+10  \n",
       "709880  6.984732e+09  9.608270e+09  1.451708e+10  2.725788e+10  \n",
       "709881  7.194539e+09  9.833215e+09  1.482454e+10  2.753897e+10  \n",
       "709882  6.945948e+09  9.630063e+09  1.432934e+10  2.676280e+10  \n",
       "\n",
       "[709883 rows x 23 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio = pd.merge(cross,fenweishu,left_on='month',right_on='month',how='left')#合并，小表往大表里填充\n",
    "portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Stkcd</th>\n",
       "      <th>month</th>\n",
       "      <th>price</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Freq</th>\n",
       "      <th>floatingvalue</th>\n",
       "      <th>totalvalue</th>\n",
       "      <th>sizef</th>\n",
       "      <th>sizet</th>\n",
       "      <th>Return</th>\n",
       "      <th>rfmonth</th>\n",
       "      <th>ret</th>\n",
       "      <th>next_ret</th>\n",
       "      <th>w</th>\n",
       "      <th>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "      <th>four</th>\n",
       "      <th>five</th>\n",
       "      <th>six</th>\n",
       "      <th>seven</th>\n",
       "      <th>eight</th>\n",
       "      <th>nine</th>\n",
       "      <th>sort</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-05-31</td>\n",
       "      <td>38.34</td>\n",
       "      <td>2</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.016010e+09</td>\n",
       "      <td>1.859497e+09</td>\n",
       "      <td>20.739149</td>\n",
       "      <td>21.343572</td>\n",
       "      <td>-0.122253</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.128345</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>1</td>\n",
       "      <td>1.310760e+07</td>\n",
       "      <td>2.075000e+07</td>\n",
       "      <td>3.930000e+07</td>\n",
       "      <td>7.435439e+07</td>\n",
       "      <td>1.237500e+08</td>\n",
       "      <td>4.656752e+08</td>\n",
       "      <td>8.200000e+08</td>\n",
       "      <td>9.495000e+08</td>\n",
       "      <td>1.179490e+09</td>\n",
       "      <td>Pmax</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-06-30</td>\n",
       "      <td>33.99</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>9.007350e+08</td>\n",
       "      <td>1.648521e+09</td>\n",
       "      <td>20.618722</td>\n",
       "      <td>21.223144</td>\n",
       "      <td>-0.113459</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>1</td>\n",
       "      <td>1.568160e+07</td>\n",
       "      <td>2.530000e+07</td>\n",
       "      <td>4.680000e+07</td>\n",
       "      <td>6.750000e+07</td>\n",
       "      <td>8.803190e+07</td>\n",
       "      <td>5.041568e+08</td>\n",
       "      <td>8.460000e+08</td>\n",
       "      <td>9.808000e+08</td>\n",
       "      <td>1.424909e+09</td>\n",
       "      <td>Pmax</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-07-31</td>\n",
       "      <td>29.54</td>\n",
       "      <td>4</td>\n",
       "      <td>16.0</td>\n",
       "      <td>7.828100e+08</td>\n",
       "      <td>1.432695e+09</td>\n",
       "      <td>20.478401</td>\n",
       "      <td>21.082823</td>\n",
       "      <td>-0.130921</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>1</td>\n",
       "      <td>1.853584e+07</td>\n",
       "      <td>3.524000e+07</td>\n",
       "      <td>4.962750e+07</td>\n",
       "      <td>7.375645e+07</td>\n",
       "      <td>2.909111e+08</td>\n",
       "      <td>6.515875e+08</td>\n",
       "      <td>7.824435e+08</td>\n",
       "      <td>9.234410e+08</td>\n",
       "      <td>1.385166e+09</td>\n",
       "      <td>Pmax</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-08-31</td>\n",
       "      <td>15.00</td>\n",
       "      <td>5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.748338e+08</td>\n",
       "      <td>1.346275e+09</td>\n",
       "      <td>20.329977</td>\n",
       "      <td>21.020607</td>\n",
       "      <td>-0.411588</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>1</td>\n",
       "      <td>3.987000e+07</td>\n",
       "      <td>4.686000e+07</td>\n",
       "      <td>5.697000e+07</td>\n",
       "      <td>1.202482e+08</td>\n",
       "      <td>2.114458e+08</td>\n",
       "      <td>5.175314e+08</td>\n",
       "      <td>7.128432e+08</td>\n",
       "      <td>1.038883e+09</td>\n",
       "      <td>1.315300e+09</td>\n",
       "      <td>Pmax</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-09-30</td>\n",
       "      <td>14.50</td>\n",
       "      <td>6</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.523394e+08</td>\n",
       "      <td>1.301399e+09</td>\n",
       "      <td>20.296075</td>\n",
       "      <td>20.986706</td>\n",
       "      <td>-0.033333</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>0.849080</td>\n",
       "      <td>1</td>\n",
       "      <td>4.695500e+07</td>\n",
       "      <td>5.084500e+07</td>\n",
       "      <td>5.776000e+07</td>\n",
       "      <td>1.127927e+08</td>\n",
       "      <td>2.007668e+08</td>\n",
       "      <td>4.029891e+08</td>\n",
       "      <td>6.602826e+08</td>\n",
       "      <td>1.001743e+09</td>\n",
       "      <td>1.268519e+09</td>\n",
       "      <td>Pmax</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709877</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-07-31</td>\n",
       "      <td>13.92</td>\n",
       "      <td>23</td>\n",
       "      <td>21.0</td>\n",
       "      <td>8.166555e+09</td>\n",
       "      <td>1.082667e+10</td>\n",
       "      <td>22.823313</td>\n",
       "      <td>23.105278</td>\n",
       "      <td>0.053747</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.052506</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>1</td>\n",
       "      <td>2.422788e+09</td>\n",
       "      <td>3.085101e+09</td>\n",
       "      <td>3.741794e+09</td>\n",
       "      <td>4.598944e+09</td>\n",
       "      <td>5.784315e+09</td>\n",
       "      <td>7.495814e+09</td>\n",
       "      <td>1.049064e+10</td>\n",
       "      <td>1.606811e+10</td>\n",
       "      <td>3.076851e+10</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709878</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>13.56</td>\n",
       "      <td>24</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.955351e+09</td>\n",
       "      <td>1.054667e+10</td>\n",
       "      <td>22.797111</td>\n",
       "      <td>23.079076</td>\n",
       "      <td>-0.025862</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>1</td>\n",
       "      <td>2.409184e+09</td>\n",
       "      <td>2.989534e+09</td>\n",
       "      <td>3.635605e+09</td>\n",
       "      <td>4.424176e+09</td>\n",
       "      <td>5.520202e+09</td>\n",
       "      <td>7.084067e+09</td>\n",
       "      <td>9.755098e+09</td>\n",
       "      <td>1.501682e+10</td>\n",
       "      <td>2.876172e+10</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709879</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>14.54</td>\n",
       "      <td>25</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.530295e+09</td>\n",
       "      <td>1.130889e+10</td>\n",
       "      <td>22.866890</td>\n",
       "      <td>23.148855</td>\n",
       "      <td>0.072271</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>1</td>\n",
       "      <td>2.421632e+09</td>\n",
       "      <td>2.985093e+09</td>\n",
       "      <td>3.638369e+09</td>\n",
       "      <td>4.403628e+09</td>\n",
       "      <td>5.487673e+09</td>\n",
       "      <td>7.058126e+09</td>\n",
       "      <td>9.799861e+09</td>\n",
       "      <td>1.484667e+10</td>\n",
       "      <td>2.831428e+10</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709880</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>13.85</td>\n",
       "      <td>26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.125488e+09</td>\n",
       "      <td>1.077222e+10</td>\n",
       "      <td>22.818272</td>\n",
       "      <td>23.100237</td>\n",
       "      <td>-0.047455</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>1</td>\n",
       "      <td>2.409577e+09</td>\n",
       "      <td>2.957719e+09</td>\n",
       "      <td>3.627091e+09</td>\n",
       "      <td>4.384522e+09</td>\n",
       "      <td>5.401911e+09</td>\n",
       "      <td>6.984732e+09</td>\n",
       "      <td>9.608270e+09</td>\n",
       "      <td>1.451708e+10</td>\n",
       "      <td>2.725788e+10</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709881</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>13.48</td>\n",
       "      <td>27</td>\n",
       "      <td>22.0</td>\n",
       "      <td>7.908417e+09</td>\n",
       "      <td>1.048444e+10</td>\n",
       "      <td>22.791193</td>\n",
       "      <td>23.073159</td>\n",
       "      <td>-0.026715</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>1</td>\n",
       "      <td>2.539108e+09</td>\n",
       "      <td>3.126053e+09</td>\n",
       "      <td>3.791893e+09</td>\n",
       "      <td>4.588888e+09</td>\n",
       "      <td>5.702116e+09</td>\n",
       "      <td>7.194539e+09</td>\n",
       "      <td>9.833215e+09</td>\n",
       "      <td>1.482454e+10</td>\n",
       "      <td>2.753897e+10</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>700739 rows × 24 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Stkcd      month  price  Rank  Freq  floatingvalue    totalvalue  \\\n",
       "0       000001 1991-05-31  38.34     2  24.0   1.016010e+09  1.859497e+09   \n",
       "1       000001 1991-06-30  33.99     3  23.0   9.007350e+08  1.648521e+09   \n",
       "2       000001 1991-07-31  29.54     4  16.0   7.828100e+08  1.432695e+09   \n",
       "3       000001 1991-08-31  15.00     5  15.0   6.748338e+08  1.346275e+09   \n",
       "4       000001 1991-09-30  14.50     6  24.0   6.523394e+08  1.301399e+09   \n",
       "...        ...        ...    ...   ...   ...            ...           ...   \n",
       "709877  605599 2023-07-31  13.92    23  21.0   8.166555e+09  1.082667e+10   \n",
       "709878  605599 2023-08-31  13.56    24  23.0   7.955351e+09  1.054667e+10   \n",
       "709879  605599 2023-09-30  14.54    25  20.0   8.530295e+09  1.130889e+10   \n",
       "709880  605599 2023-10-31  13.85    26  17.0   8.125488e+09  1.077222e+10   \n",
       "709881  605599 2023-11-30  13.48    27  22.0   7.908417e+09  1.048444e+10   \n",
       "\n",
       "            sizef      sizet    Return   rfmonth       ret  next_ret  w  \\\n",
       "0       20.739149  21.343572 -0.122253  0.006092 -0.128345 -0.119551  1   \n",
       "1       20.618722  21.223144 -0.113459  0.006092 -0.119551 -0.137013  1   \n",
       "2       20.478401  21.082823 -0.130921  0.006092 -0.137013 -0.417680  1   \n",
       "3       20.329977  21.020607 -0.411588  0.006092 -0.417680 -0.039425  1   \n",
       "4       20.296075  20.986706 -0.033333  0.006092 -0.039425  0.849080  1   \n",
       "...           ...        ...       ...       ...       ...       ... ..   \n",
       "709877  22.823313  23.105278  0.053747  0.001241  0.052506 -0.027103  1   \n",
       "709878  22.797111  23.079076 -0.025862  0.001241 -0.027103  0.071030  1   \n",
       "709879  22.866890  23.148855  0.072271  0.001241  0.071030 -0.048696  1   \n",
       "709880  22.818272  23.100237 -0.047455  0.001241 -0.048696 -0.027956  1   \n",
       "709881  22.791193  23.073159 -0.026715  0.001241 -0.027956  0.103358  1   \n",
       "\n",
       "                 one           two         three          four          five  \\\n",
       "0       1.310760e+07  2.075000e+07  3.930000e+07  7.435439e+07  1.237500e+08   \n",
       "1       1.568160e+07  2.530000e+07  4.680000e+07  6.750000e+07  8.803190e+07   \n",
       "2       1.853584e+07  3.524000e+07  4.962750e+07  7.375645e+07  2.909111e+08   \n",
       "3       3.987000e+07  4.686000e+07  5.697000e+07  1.202482e+08  2.114458e+08   \n",
       "4       4.695500e+07  5.084500e+07  5.776000e+07  1.127927e+08  2.007668e+08   \n",
       "...              ...           ...           ...           ...           ...   \n",
       "709877  2.422788e+09  3.085101e+09  3.741794e+09  4.598944e+09  5.784315e+09   \n",
       "709878  2.409184e+09  2.989534e+09  3.635605e+09  4.424176e+09  5.520202e+09   \n",
       "709879  2.421632e+09  2.985093e+09  3.638369e+09  4.403628e+09  5.487673e+09   \n",
       "709880  2.409577e+09  2.957719e+09  3.627091e+09  4.384522e+09  5.401911e+09   \n",
       "709881  2.539108e+09  3.126053e+09  3.791893e+09  4.588888e+09  5.702116e+09   \n",
       "\n",
       "                 six         seven         eight          nine  sort  \n",
       "0       4.656752e+08  8.200000e+08  9.495000e+08  1.179490e+09  Pmax  \n",
       "1       5.041568e+08  8.460000e+08  9.808000e+08  1.424909e+09  Pmax  \n",
       "2       6.515875e+08  7.824435e+08  9.234410e+08  1.385166e+09  Pmax  \n",
       "3       5.175314e+08  7.128432e+08  1.038883e+09  1.315300e+09  Pmax  \n",
       "4       4.029891e+08  6.602826e+08  1.001743e+09  1.268519e+09  Pmax  \n",
       "...              ...           ...           ...           ...   ...  \n",
       "709877  7.495814e+09  1.049064e+10  1.606811e+10  3.076851e+10    P8  \n",
       "709878  7.084067e+09  9.755098e+09  1.501682e+10  2.876172e+10    P8  \n",
       "709879  7.058126e+09  9.799861e+09  1.484667e+10  2.831428e+10    P8  \n",
       "709880  6.984732e+09  9.608270e+09  1.451708e+10  2.725788e+10    P8  \n",
       "709881  7.194539e+09  9.833215e+09  1.482454e+10  2.753897e+10    P8  \n",
       "\n",
       "[700739 rows x 24 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# where if else (if else)\n",
    "portfolio['sort'] = np.where(\n",
    "    portfolio['totalvalue'] <= portfolio['one'], 'P1',\n",
    "    np.where(\n",
    "        portfolio['totalvalue'] <= portfolio['two'], 'P2',\n",
    "        np.where(\n",
    "            portfolio['totalvalue'] <= portfolio['three'], 'P3',\n",
    "            np.where(\n",
    "                portfolio['totalvalue'] <= portfolio['four'], 'P4',\n",
    "                np.where(\n",
    "                    portfolio['totalvalue'] <= portfolio['five'], 'P5',\n",
    "                    np.where(\n",
    "                        portfolio['totalvalue'] <= portfolio['six'], 'P6',\n",
    "                        np.where(\n",
    "                            portfolio['totalvalue'] <= portfolio['seven'], 'P7',\n",
    "                            np.where(\n",
    "                                portfolio['totalvalue'] <= portfolio['eight'], 'P8',\n",
    "                                np.where(\n",
    "                                    portfolio['totalvalue'] <= portfolio['nine'],\n",
    "                                    'P9', 'Pmax')))))))))#生成了新的列sort\n",
    "portfolio = portfolio.dropna(subset=['floatingvalue','next_ret'])#把缺失值丢掉，'next_ret','floatingvalue'中不能有缺失值\n",
    "portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th>0</th>\n",
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       "      <th>month</th>\n",
       "      <th>sort</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">1991-01-31</th>\n",
       "      <th>P1</th>\n",
       "      <td>0.028134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P2</th>\n",
       "      <td>-0.041567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P4</th>\n",
       "      <td>0.081305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P6</th>\n",
       "      <td>0.038284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P8</th>\n",
       "      <td>-0.002070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">2023-11-30</th>\n",
       "      <th>P6</th>\n",
       "      <td>-0.029353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P7</th>\n",
       "      <td>-0.035430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P8</th>\n",
       "      <td>-0.029991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>P9</th>\n",
       "      <td>-0.028759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Pmax</th>\n",
       "      <td>-0.017816</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3946 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        0\n",
       "month      sort          \n",
       "1991-01-31 P1    0.028134\n",
       "           P2   -0.041567\n",
       "           P4    0.081305\n",
       "           P6    0.038284\n",
       "           P8   -0.002070\n",
       "...                   ...\n",
       "2023-11-30 P6   -0.029353\n",
       "           P7   -0.035430\n",
       "           P8   -0.029991\n",
       "           P9   -0.028759\n",
       "           Pmax -0.017816\n",
       "\n",
       "[3946 rows x 1 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 计算每个股票每个月市值加权下一个月的回报率\n",
    "portfolio_size =  pd.DataFrame(portfolio.groupby(['month','sort']).apply(\n",
    "    lambda x: np.average(x['next_ret'],weights = x['totalvalue']),include_groups=False))#权重是总市值\n",
    "portfolio_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>sort</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P1</td>\n",
       "      <td>0.028134</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P2</td>\n",
       "      <td>-0.041567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P4</td>\n",
       "      <td>0.081305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P6</td>\n",
       "      <td>0.038284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P8</td>\n",
       "      <td>-0.002070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3941</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P6</td>\n",
       "      <td>-0.029353</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3942</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P7</td>\n",
       "      <td>-0.035430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3943</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P8</td>\n",
       "      <td>-0.029991</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3944</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P9</td>\n",
       "      <td>-0.028759</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3945</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>Pmax</td>\n",
       "      <td>-0.017816</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3946 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          month  sort         p\n",
       "0    1991-02-28    P1  0.028134\n",
       "1    1991-02-28    P2 -0.041567\n",
       "2    1991-02-28    P4  0.081305\n",
       "3    1991-02-28    P6  0.038284\n",
       "4    1991-02-28    P8 -0.002070\n",
       "...         ...   ...       ...\n",
       "3941 2023-12-31    P6 -0.029353\n",
       "3942 2023-12-31    P7 -0.035430\n",
       "3943 2023-12-31    P8 -0.029991\n",
       "3944 2023-12-31    P9 -0.028759\n",
       "3945 2023-12-31  Pmax -0.017816\n",
       "\n",
       "[3946 rows x 3 columns]"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_size = portfolio_size.reset_index()#去掉索引\n",
    "portfolio_size.columns = ['month', 'sort', 'p']#改名\n",
    "portfolio_size['month'] = portfolio_size['month'] + MonthEnd(1)#月份加一\n",
    "portfolio_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sort</th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
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       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1991-02-28</th>\n",
       "      <td>0.028134</td>\n",
       "      <td>-0.041567</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.081305</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.038284</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010496</td>\n",
       "      <td>0.017638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-03-31</th>\n",
       "      <td>0.070941</td>\n",
       "      <td>-0.069140</td>\n",
       "      <td>-0.059149</td>\n",
       "      <td>-0.070455</td>\n",
       "      <td>-0.133253</td>\n",
       "      <td>-0.044343</td>\n",
       "      <td>-0.133504</td>\n",
       "      <td>0.023904</td>\n",
       "      <td>-0.125264</td>\n",
       "      <td>-0.133293</td>\n",
       "      <td>0.204234</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-04-30</th>\n",
       "      <td>0.087227</td>\n",
       "      <td>-0.000595</td>\n",
       "      <td>0.070484</td>\n",
       "      <td>-0.097744</td>\n",
       "      <td>-0.133193</td>\n",
       "      <td>-0.103582</td>\n",
       "      <td>-0.122736</td>\n",
       "      <td>0.120035</td>\n",
       "      <td>-0.077512</td>\n",
       "      <td>-0.123391</td>\n",
       "      <td>0.210618</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-05-31</th>\n",
       "      <td>0.202117</td>\n",
       "      <td>0.080639</td>\n",
       "      <td>0.055289</td>\n",
       "      <td>-0.130814</td>\n",
       "      <td>-0.006657</td>\n",
       "      <td>-0.120582</td>\n",
       "      <td>-0.036993</td>\n",
       "      <td>-0.031989</td>\n",
       "      <td>0.238572</td>\n",
       "      <td>-0.129118</td>\n",
       "      <td>0.331235</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-06-30</th>\n",
       "      <td>0.186315</td>\n",
       "      <td>0.213185</td>\n",
       "      <td>0.184748</td>\n",
       "      <td>0.177858</td>\n",
       "      <td>-0.460637</td>\n",
       "      <td>-0.309901</td>\n",
       "      <td>0.190006</td>\n",
       "      <td>-0.115097</td>\n",
       "      <td>0.201980</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>0.305866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>0.001526</td>\n",
       "      <td>-0.007487</td>\n",
       "      <td>-0.027998</td>\n",
       "      <td>-0.040304</td>\n",
       "      <td>-0.043932</td>\n",
       "      <td>-0.057348</td>\n",
       "      <td>-0.060162</td>\n",
       "      <td>-0.066902</td>\n",
       "      <td>-0.060407</td>\n",
       "      <td>-0.057794</td>\n",
       "      <td>0.059319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>0.020277</td>\n",
       "      <td>0.014331</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>-0.009448</td>\n",
       "      <td>-0.003383</td>\n",
       "      <td>0.004828</td>\n",
       "      <td>-0.007206</td>\n",
       "      <td>-0.008534</td>\n",
       "      <td>-0.012221</td>\n",
       "      <td>0.032498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>0.008199</td>\n",
       "      <td>0.006227</td>\n",
       "      <td>-0.003861</td>\n",
       "      <td>-0.001851</td>\n",
       "      <td>-0.004907</td>\n",
       "      <td>-0.010312</td>\n",
       "      <td>-0.019380</td>\n",
       "      <td>-0.028806</td>\n",
       "      <td>-0.025160</td>\n",
       "      <td>-0.033507</td>\n",
       "      <td>0.041706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>0.063053</td>\n",
       "      <td>0.058229</td>\n",
       "      <td>0.054380</td>\n",
       "      <td>0.040258</td>\n",
       "      <td>0.050403</td>\n",
       "      <td>0.038414</td>\n",
       "      <td>0.025098</td>\n",
       "      <td>0.013146</td>\n",
       "      <td>0.002612</td>\n",
       "      <td>-0.013457</td>\n",
       "      <td>0.076511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.005808</td>\n",
       "      <td>-0.005787</td>\n",
       "      <td>-0.011312</td>\n",
       "      <td>-0.016412</td>\n",
       "      <td>-0.031357</td>\n",
       "      <td>-0.029353</td>\n",
       "      <td>-0.035430</td>\n",
       "      <td>-0.029991</td>\n",
       "      <td>-0.028759</td>\n",
       "      <td>-0.017816</td>\n",
       "      <td>0.012008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>395 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sort              P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1991-02-28  0.028134 -0.041567       NaN  0.081305       NaN  0.038284   \n",
       "1991-03-31  0.070941 -0.069140 -0.059149 -0.070455 -0.133253 -0.044343   \n",
       "1991-04-30  0.087227 -0.000595  0.070484 -0.097744 -0.133193 -0.103582   \n",
       "1991-05-31  0.202117  0.080639  0.055289 -0.130814 -0.006657 -0.120582   \n",
       "1991-06-30  0.186315  0.213185  0.184748  0.177858 -0.460637 -0.309901   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31  0.001526 -0.007487 -0.027998 -0.040304 -0.043932 -0.057348   \n",
       "2023-09-30  0.020277  0.014331 -0.000218  0.001945 -0.009448 -0.003383   \n",
       "2023-10-31  0.008199  0.006227 -0.003861 -0.001851 -0.004907 -0.010312   \n",
       "2023-11-30  0.063053  0.058229  0.054380  0.040258  0.050403  0.038414   \n",
       "2023-12-31 -0.005808 -0.005787 -0.011312 -0.016412 -0.031357 -0.029353   \n",
       "\n",
       "sort              P7        P8        P9      Pmax  My_portfolio  \n",
       "month                                                             \n",
       "1991-02-28       NaN -0.002070       NaN  0.010496      0.017638  \n",
       "1991-03-31 -0.133504  0.023904 -0.125264 -0.133293      0.204234  \n",
       "1991-04-30 -0.122736  0.120035 -0.077512 -0.123391      0.210618  \n",
       "1991-05-31 -0.036993 -0.031989  0.238572 -0.129118      0.331235  \n",
       "1991-06-30  0.190006 -0.115097  0.201980 -0.119551      0.305866  \n",
       "...              ...       ...       ...       ...           ...  \n",
       "2023-08-31 -0.060162 -0.066902 -0.060407 -0.057794      0.059319  \n",
       "2023-09-30  0.004828 -0.007206 -0.008534 -0.012221      0.032498  \n",
       "2023-10-31 -0.019380 -0.028806 -0.025160 -0.033507      0.041706  \n",
       "2023-11-30  0.025098  0.013146  0.002612 -0.013457      0.076511  \n",
       "2023-12-31 -0.035430 -0.029991 -0.028759 -0.017816      0.012008  \n",
       "\n",
       "[395 rows x 11 columns]"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_size = portfolio_size.pivot_table(index='month',columns='sort', values='p')#长数据变成宽数据，按照month来放，按sort作为新列名，里面放的值是组合收益率p\n",
    "portfolio_size['My_portfolio'] = portfolio_size['P1'] - portfolio_size['Pmax']#买小size，卖大size\n",
    "portfolio_size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sort</th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
       "      <th>P5</th>\n",
       "      <th>P6</th>\n",
       "      <th>P7</th>\n",
       "      <th>P8</th>\n",
       "      <th>P9</th>\n",
       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.145162</td>\n",
       "      <td>-0.133811</td>\n",
       "      <td>-0.131991</td>\n",
       "      <td>-0.141603</td>\n",
       "      <td>-0.138500</td>\n",
       "      <td>-0.129420</td>\n",
       "      <td>-0.125187</td>\n",
       "      <td>-0.133302</td>\n",
       "      <td>-0.142752</td>\n",
       "      <td>-0.131525</td>\n",
       "      <td>-0.013637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>-0.014135</td>\n",
       "      <td>-0.016487</td>\n",
       "      <td>-0.026105</td>\n",
       "      <td>-0.013507</td>\n",
       "      <td>-0.027373</td>\n",
       "      <td>-0.031945</td>\n",
       "      <td>-0.013020</td>\n",
       "      <td>-0.020658</td>\n",
       "      <td>-0.028212</td>\n",
       "      <td>-0.030146</td>\n",
       "      <td>0.016012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>0.145888</td>\n",
       "      <td>0.124613</td>\n",
       "      <td>0.137706</td>\n",
       "      <td>0.151517</td>\n",
       "      <td>0.172736</td>\n",
       "      <td>0.151145</td>\n",
       "      <td>0.132809</td>\n",
       "      <td>0.102804</td>\n",
       "      <td>0.128072</td>\n",
       "      <td>0.160310</td>\n",
       "      <td>-0.014422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>-0.129085</td>\n",
       "      <td>-0.117482</td>\n",
       "      <td>-0.104661</td>\n",
       "      <td>-0.114248</td>\n",
       "      <td>-0.100667</td>\n",
       "      <td>-0.092057</td>\n",
       "      <td>-0.118221</td>\n",
       "      <td>-0.123341</td>\n",
       "      <td>-0.095764</td>\n",
       "      <td>-0.112655</td>\n",
       "      <td>-0.016430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.240024</td>\n",
       "      <td>0.178908</td>\n",
       "      <td>0.238830</td>\n",
       "      <td>0.196759</td>\n",
       "      <td>0.179584</td>\n",
       "      <td>0.196451</td>\n",
       "      <td>0.163534</td>\n",
       "      <td>0.179333</td>\n",
       "      <td>0.203274</td>\n",
       "      <td>0.156261</td>\n",
       "      <td>0.083763</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>0.001526</td>\n",
       "      <td>-0.007487</td>\n",
       "      <td>-0.027998</td>\n",
       "      <td>-0.040304</td>\n",
       "      <td>-0.043932</td>\n",
       "      <td>-0.057348</td>\n",
       "      <td>-0.060162</td>\n",
       "      <td>-0.066902</td>\n",
       "      <td>-0.060407</td>\n",
       "      <td>-0.057794</td>\n",
       "      <td>0.059319</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>0.020277</td>\n",
       "      <td>0.014331</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>-0.009448</td>\n",
       "      <td>-0.003383</td>\n",
       "      <td>0.004828</td>\n",
       "      <td>-0.007206</td>\n",
       "      <td>-0.008534</td>\n",
       "      <td>-0.012221</td>\n",
       "      <td>0.032498</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>0.008199</td>\n",
       "      <td>0.006227</td>\n",
       "      <td>-0.003861</td>\n",
       "      <td>-0.001851</td>\n",
       "      <td>-0.004907</td>\n",
       "      <td>-0.010312</td>\n",
       "      <td>-0.019380</td>\n",
       "      <td>-0.028806</td>\n",
       "      <td>-0.025160</td>\n",
       "      <td>-0.033507</td>\n",
       "      <td>0.041706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>0.063053</td>\n",
       "      <td>0.058229</td>\n",
       "      <td>0.054380</td>\n",
       "      <td>0.040258</td>\n",
       "      <td>0.050403</td>\n",
       "      <td>0.038414</td>\n",
       "      <td>0.025098</td>\n",
       "      <td>0.013146</td>\n",
       "      <td>0.002612</td>\n",
       "      <td>-0.013457</td>\n",
       "      <td>0.076511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.005808</td>\n",
       "      <td>-0.005787</td>\n",
       "      <td>-0.011312</td>\n",
       "      <td>-0.016412</td>\n",
       "      <td>-0.031357</td>\n",
       "      <td>-0.029353</td>\n",
       "      <td>-0.035430</td>\n",
       "      <td>-0.029991</td>\n",
       "      <td>-0.028759</td>\n",
       "      <td>-0.017816</td>\n",
       "      <td>0.012008</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>348 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sort              P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1995-01-31 -0.145162 -0.133811 -0.131991 -0.141603 -0.138500 -0.129420   \n",
       "1995-02-28 -0.014135 -0.016487 -0.026105 -0.013507 -0.027373 -0.031945   \n",
       "1995-03-31  0.145888  0.124613  0.137706  0.151517  0.172736  0.151145   \n",
       "1995-04-30 -0.129085 -0.117482 -0.104661 -0.114248 -0.100667 -0.092057   \n",
       "1995-05-31  0.240024  0.178908  0.238830  0.196759  0.179584  0.196451   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31  0.001526 -0.007487 -0.027998 -0.040304 -0.043932 -0.057348   \n",
       "2023-09-30  0.020277  0.014331 -0.000218  0.001945 -0.009448 -0.003383   \n",
       "2023-10-31  0.008199  0.006227 -0.003861 -0.001851 -0.004907 -0.010312   \n",
       "2023-11-30  0.063053  0.058229  0.054380  0.040258  0.050403  0.038414   \n",
       "2023-12-31 -0.005808 -0.005787 -0.011312 -0.016412 -0.031357 -0.029353   \n",
       "\n",
       "sort              P7        P8        P9      Pmax  My_portfolio  \n",
       "month                                                             \n",
       "1995-01-31 -0.125187 -0.133302 -0.142752 -0.131525     -0.013637  \n",
       "1995-02-28 -0.013020 -0.020658 -0.028212 -0.030146      0.016012  \n",
       "1995-03-31  0.132809  0.102804  0.128072  0.160310     -0.014422  \n",
       "1995-04-30 -0.118221 -0.123341 -0.095764 -0.112655     -0.016430  \n",
       "1995-05-31  0.163534  0.179333  0.203274  0.156261      0.083763  \n",
       "...              ...       ...       ...       ...           ...  \n",
       "2023-08-31 -0.060162 -0.066902 -0.060407 -0.057794      0.059319  \n",
       "2023-09-30  0.004828 -0.007206 -0.008534 -0.012221      0.032498  \n",
       "2023-10-31 -0.019380 -0.028806 -0.025160 -0.033507      0.041706  \n",
       "2023-11-30  0.025098  0.013146  0.002612 -0.013457      0.076511  \n",
       "2023-12-31 -0.035430 -0.029991 -0.028759 -0.017816      0.012008  \n",
       "\n",
       "[348 rows x 11 columns]"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_size = portfolio_size['1995':'2023']# 选取1995年后的时间段\n",
    "portfolio_size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#  Size 表现"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:           My_portfolio   R-squared:                       0.000\n",
      "Model:                            OLS   Adj. R-squared:                  0.000\n",
      "Method:                 Least Squares   F-statistic:                       nan\n",
      "Date:                Wed, 11 Dec 2024   Prob (F-statistic):                nan\n",
      "Time:                        14:38:41   Log-Likelihood:                 363.04\n",
      "No. Observations:                 348   AIC:                            -724.1\n",
      "Df Residuals:                     347   BIC:                            -720.2\n",
      "Df Model:                           0                                         \n",
      "Covariance Type:                  HAC                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0208      0.005      4.511      0.000       0.012       0.030\n",
      "==============================================================================\n",
      "Omnibus:                       31.539   Durbin-Watson:                   1.815\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              108.980\n",
      "Skew:                          -0.292   Prob(JB):                     2.16e-24\n",
      "Kurtosis:                       5.678   Cond. No.                         1.00\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors are heteroscedasticity and autocorrelation robust (HAC) using 6 lags and without small sample correction\n"
     ]
    }
   ],
   "source": [
    "model_size = smf.ols('My_portfolio ~ 1',data=portfolio_size['1995':'2023']).fit(   # 把投资策略回归到1上\n",
    "    cov_type='HAC', cov_kwds={'maxlags': 6})\n",
    "print(model_size.summary())\n",
    "# 回归的结果和直接做均值t检验的结果是一样的"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "平均每月获得2%的收益率，非常高了"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Preclose</th>\n",
       "      <th>Open</th>\n",
       "      <th>Highest</th>\n",
       "      <th>Lowest</th>\n",
       "      <th>Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>Money</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Day</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1990-12-19</th>\n",
       "      <td></td>\n",
       "      <td>96.050</td>\n",
       "      <td>99.980</td>\n",
       "      <td>95.790</td>\n",
       "      <td>99.980</td>\n",
       "      <td>126000.00</td>\n",
       "      <td>4.940000e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-20</th>\n",
       "      <td>99.98</td>\n",
       "      <td>104.300</td>\n",
       "      <td>104.390</td>\n",
       "      <td>99.980</td>\n",
       "      <td>104.390</td>\n",
       "      <td>19700.00</td>\n",
       "      <td>8.400000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-21</th>\n",
       "      <td>104.39</td>\n",
       "      <td>109.070</td>\n",
       "      <td>109.130</td>\n",
       "      <td>103.730</td>\n",
       "      <td>109.130</td>\n",
       "      <td>2800.00</td>\n",
       "      <td>1.600000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-24</th>\n",
       "      <td>109.13</td>\n",
       "      <td>113.570</td>\n",
       "      <td>114.550</td>\n",
       "      <td>109.130</td>\n",
       "      <td>114.550</td>\n",
       "      <td>3200.00</td>\n",
       "      <td>3.100000e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1990-12-25</th>\n",
       "      <td>114.55</td>\n",
       "      <td>120.090</td>\n",
       "      <td>120.250</td>\n",
       "      <td>114.550</td>\n",
       "      <td>120.250</td>\n",
       "      <td>1500.00</td>\n",
       "      <td>6.000000e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-24</th>\n",
       "      <td>2748.918</td>\n",
       "      <td>2770.754</td>\n",
       "      <td>2863.152</td>\n",
       "      <td>2761.372</td>\n",
       "      <td>2863.126</td>\n",
       "      <td>4776195.45</td>\n",
       "      <td>4.427953e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-25</th>\n",
       "      <td>2863.126</td>\n",
       "      <td>2901.419</td>\n",
       "      <td>2952.451</td>\n",
       "      <td>2889.048</td>\n",
       "      <td>2896.306</td>\n",
       "      <td>5682598.16</td>\n",
       "      <td>5.166981e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-26</th>\n",
       "      <td>2896.306</td>\n",
       "      <td>2893.745</td>\n",
       "      <td>3000.953</td>\n",
       "      <td>2889.014</td>\n",
       "      <td>3000.953</td>\n",
       "      <td>5763192.61</td>\n",
       "      <td>5.246691e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-27</th>\n",
       "      <td>3000.953</td>\n",
       "      <td>3049.103</td>\n",
       "      <td>3087.529</td>\n",
       "      <td>3017.445</td>\n",
       "      <td>3087.529</td>\n",
       "      <td>4922871.63</td>\n",
       "      <td>4.806126e+07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
       "      <td>3087.529</td>\n",
       "      <td>3194.722</td>\n",
       "      <td>3358.588</td>\n",
       "      <td>3153.697</td>\n",
       "      <td>3336.497</td>\n",
       "      <td>11023379.17</td>\n",
       "      <td>1.167773e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>8251 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Preclose      Open   Highest    Lowest     Close       Volume  \\\n",
       "Day                                                                         \n",
       "1990-12-19              96.050    99.980    95.790    99.980    126000.00   \n",
       "1990-12-20     99.98   104.300   104.390    99.980   104.390     19700.00   \n",
       "1990-12-21    104.39   109.070   109.130   103.730   109.130      2800.00   \n",
       "1990-12-24    109.13   113.570   114.550   109.130   114.550      3200.00   \n",
       "1990-12-25    114.55   120.090   120.250   114.550   120.250      1500.00   \n",
       "...              ...       ...       ...       ...       ...          ...   \n",
       "2024-09-24  2748.918  2770.754  2863.152  2761.372  2863.126   4776195.45   \n",
       "2024-09-25  2863.126  2901.419  2952.451  2889.048  2896.306   5682598.16   \n",
       "2024-09-26  2896.306  2893.745  3000.953  2889.014  3000.953   5763192.61   \n",
       "2024-09-27  3000.953  3049.103  3087.529  3017.445  3087.529   4922871.63   \n",
       "2024-09-30  3087.529  3194.722  3358.588  3153.697  3336.497  11023379.17   \n",
       "\n",
       "                   Money  \n",
       "Day                       \n",
       "1990-12-19  4.940000e+05  \n",
       "1990-12-20  8.400000e+04  \n",
       "1990-12-21  1.600000e+04  \n",
       "1990-12-24  3.100000e+04  \n",
       "1990-12-25  6.000000e+03  \n",
       "...                  ...  \n",
       "2024-09-24  4.427953e+07  \n",
       "2024-09-25  5.166981e+07  \n",
       "2024-09-26  5.246691e+07  \n",
       "2024-09-27  4.806126e+07  \n",
       "2024-09-30  1.167773e+08  \n",
       "\n",
       "[8251 rows x 7 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Raw_return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.131631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>-0.023694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>0.177803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>-0.103552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.207922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-05-31</th>\n",
       "      <td>-0.005801</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-06-30</th>\n",
       "      <td>-0.038684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-07-31</th>\n",
       "      <td>-0.009656</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-31</th>\n",
       "      <td>-0.032849</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-30</th>\n",
       "      <td>0.173908</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>357 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Raw_return\n",
       "month                 \n",
       "1995-01-31   -0.131631\n",
       "1995-02-28   -0.023694\n",
       "1995-03-31    0.177803\n",
       "1995-04-30   -0.103552\n",
       "1995-05-31    0.207922\n",
       "...                ...\n",
       "2024-05-31   -0.005801\n",
       "2024-06-30   -0.038684\n",
       "2024-07-31   -0.009656\n",
       "2024-08-31   -0.032849\n",
       "2024-09-30    0.173908\n",
       "\n",
       "[357 rows x 1 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"D:/python-homework/python-homework/000001.csv\")# 导入大盘数据\n",
    "data['Day'] = pd.to_datetime(data['Day'],format='%Y/%m/%d')# 改变格式\n",
    "data.set_index('Day', inplace = True)# 设置索引\n",
    "data.sort_values(by = ['Day'],axis=0, ascending=True)# 排序\n",
    "data_new = data['1995-01':'2024-09'].copy()#截取一段时间\n",
    "data_new['Close'] = pd.to_numeric(data_new['Close'])\n",
    "data_new['Preclose'] = pd.to_numeric(data_new['Preclose'])\n",
    "data_new['Raw_return'] = data_new['Close'] / data_new['Preclose'] - 1\n",
    "Month_data = data_new.resample('ME')['Raw_return'].apply(lambda x: (1+x).prod() - 1).to_frame()#得到月的收益率\n",
    "Month_data.reset_index(inplace = True)# 去掉索引 \n",
    "Month_data.rename(columns = {'Day':'month'}, inplace = True)#重命名\n",
    "Month_data.set_index('month', inplace = True)#设置索引\n",
    "Month_data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "关心该投资策略和大盘的关系"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
       "      <th>P5</th>\n",
       "      <th>P6</th>\n",
       "      <th>P7</th>\n",
       "      <th>P8</th>\n",
       "      <th>P9</th>\n",
       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "      <th>Raw_return</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.145162</td>\n",
       "      <td>-0.133811</td>\n",
       "      <td>-0.131991</td>\n",
       "      <td>-0.141603</td>\n",
       "      <td>-0.138500</td>\n",
       "      <td>-0.129420</td>\n",
       "      <td>-0.125187</td>\n",
       "      <td>-0.133302</td>\n",
       "      <td>-0.142752</td>\n",
       "      <td>-0.131525</td>\n",
       "      <td>-0.013637</td>\n",
       "      <td>-0.131631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>-0.014135</td>\n",
       "      <td>-0.016487</td>\n",
       "      <td>-0.026105</td>\n",
       "      <td>-0.013507</td>\n",
       "      <td>-0.027373</td>\n",
       "      <td>-0.031945</td>\n",
       "      <td>-0.013020</td>\n",
       "      <td>-0.020658</td>\n",
       "      <td>-0.028212</td>\n",
       "      <td>-0.030146</td>\n",
       "      <td>0.016012</td>\n",
       "      <td>-0.023694</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>0.145888</td>\n",
       "      <td>0.124613</td>\n",
       "      <td>0.137706</td>\n",
       "      <td>0.151517</td>\n",
       "      <td>0.172736</td>\n",
       "      <td>0.151145</td>\n",
       "      <td>0.132809</td>\n",
       "      <td>0.102804</td>\n",
       "      <td>0.128072</td>\n",
       "      <td>0.160310</td>\n",
       "      <td>-0.014422</td>\n",
       "      <td>0.177803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>-0.129085</td>\n",
       "      <td>-0.117482</td>\n",
       "      <td>-0.104661</td>\n",
       "      <td>-0.114248</td>\n",
       "      <td>-0.100667</td>\n",
       "      <td>-0.092057</td>\n",
       "      <td>-0.118221</td>\n",
       "      <td>-0.123341</td>\n",
       "      <td>-0.095764</td>\n",
       "      <td>-0.112655</td>\n",
       "      <td>-0.016430</td>\n",
       "      <td>-0.103552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.240024</td>\n",
       "      <td>0.178908</td>\n",
       "      <td>0.238830</td>\n",
       "      <td>0.196759</td>\n",
       "      <td>0.179584</td>\n",
       "      <td>0.196451</td>\n",
       "      <td>0.163534</td>\n",
       "      <td>0.179333</td>\n",
       "      <td>0.203274</td>\n",
       "      <td>0.156261</td>\n",
       "      <td>0.083763</td>\n",
       "      <td>0.207922</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>0.001526</td>\n",
       "      <td>-0.007487</td>\n",
       "      <td>-0.027998</td>\n",
       "      <td>-0.040304</td>\n",
       "      <td>-0.043932</td>\n",
       "      <td>-0.057348</td>\n",
       "      <td>-0.060162</td>\n",
       "      <td>-0.066902</td>\n",
       "      <td>-0.060407</td>\n",
       "      <td>-0.057794</td>\n",
       "      <td>0.059319</td>\n",
       "      <td>-0.052009</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>0.020277</td>\n",
       "      <td>0.014331</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>-0.009448</td>\n",
       "      <td>-0.003383</td>\n",
       "      <td>0.004828</td>\n",
       "      <td>-0.007206</td>\n",
       "      <td>-0.008534</td>\n",
       "      <td>-0.012221</td>\n",
       "      <td>0.032498</td>\n",
       "      <td>-0.003013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>0.008199</td>\n",
       "      <td>0.006227</td>\n",
       "      <td>-0.003861</td>\n",
       "      <td>-0.001851</td>\n",
       "      <td>-0.004907</td>\n",
       "      <td>-0.010312</td>\n",
       "      <td>-0.019380</td>\n",
       "      <td>-0.028806</td>\n",
       "      <td>-0.025160</td>\n",
       "      <td>-0.033507</td>\n",
       "      <td>0.041706</td>\n",
       "      <td>-0.029483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>0.063053</td>\n",
       "      <td>0.058229</td>\n",
       "      <td>0.054380</td>\n",
       "      <td>0.040258</td>\n",
       "      <td>0.050403</td>\n",
       "      <td>0.038414</td>\n",
       "      <td>0.025098</td>\n",
       "      <td>0.013146</td>\n",
       "      <td>0.002612</td>\n",
       "      <td>-0.013457</td>\n",
       "      <td>0.076511</td>\n",
       "      <td>0.003611</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.005808</td>\n",
       "      <td>-0.005787</td>\n",
       "      <td>-0.011312</td>\n",
       "      <td>-0.016412</td>\n",
       "      <td>-0.031357</td>\n",
       "      <td>-0.029353</td>\n",
       "      <td>-0.035430</td>\n",
       "      <td>-0.029991</td>\n",
       "      <td>-0.028759</td>\n",
       "      <td>-0.017816</td>\n",
       "      <td>0.012008</td>\n",
       "      <td>-0.018067</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>348 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1995-01-31 -0.145162 -0.133811 -0.131991 -0.141603 -0.138500 -0.129420   \n",
       "1995-02-28 -0.014135 -0.016487 -0.026105 -0.013507 -0.027373 -0.031945   \n",
       "1995-03-31  0.145888  0.124613  0.137706  0.151517  0.172736  0.151145   \n",
       "1995-04-30 -0.129085 -0.117482 -0.104661 -0.114248 -0.100667 -0.092057   \n",
       "1995-05-31  0.240024  0.178908  0.238830  0.196759  0.179584  0.196451   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31  0.001526 -0.007487 -0.027998 -0.040304 -0.043932 -0.057348   \n",
       "2023-09-30  0.020277  0.014331 -0.000218  0.001945 -0.009448 -0.003383   \n",
       "2023-10-31  0.008199  0.006227 -0.003861 -0.001851 -0.004907 -0.010312   \n",
       "2023-11-30  0.063053  0.058229  0.054380  0.040258  0.050403  0.038414   \n",
       "2023-12-31 -0.005808 -0.005787 -0.011312 -0.016412 -0.031357 -0.029353   \n",
       "\n",
       "                  P7        P8        P9      Pmax  My_portfolio  Raw_return  \n",
       "month                                                                         \n",
       "1995-01-31 -0.125187 -0.133302 -0.142752 -0.131525     -0.013637   -0.131631  \n",
       "1995-02-28 -0.013020 -0.020658 -0.028212 -0.030146      0.016012   -0.023694  \n",
       "1995-03-31  0.132809  0.102804  0.128072  0.160310     -0.014422    0.177803  \n",
       "1995-04-30 -0.118221 -0.123341 -0.095764 -0.112655     -0.016430   -0.103552  \n",
       "1995-05-31  0.163534  0.179333  0.203274  0.156261      0.083763    0.207922  \n",
       "...              ...       ...       ...       ...           ...         ...  \n",
       "2023-08-31 -0.060162 -0.066902 -0.060407 -0.057794      0.059319   -0.052009  \n",
       "2023-09-30  0.004828 -0.007206 -0.008534 -0.012221      0.032498   -0.003013  \n",
       "2023-10-31 -0.019380 -0.028806 -0.025160 -0.033507      0.041706   -0.029483  \n",
       "2023-11-30  0.025098  0.013146  0.002612 -0.013457      0.076511    0.003611  \n",
       "2023-12-31 -0.035430 -0.029991 -0.028759 -0.017816      0.012008   -0.018067  \n",
       "\n",
       "[348 rows x 12 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "MYPORT = pd.merge(portfolio_size,Month_data,left_index=True,right_index=True,how='left')# 把收益率和大盘合并起来\n",
    "MYPORT = MYPORT['1995':'2023']\n",
    "MYPORT\n",
    "# 一列是我的策略，一列是大盘"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Size是$\\beta$还是$\\alpha$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$\\beta$策略承担的是大盘的风险"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:           My_portfolio   R-squared:                       0.001\n",
      "Model:                            OLS   Adj. R-squared:                 -0.002\n",
      "Method:                 Least Squares   F-statistic:                   0.08494\n",
      "Date:                Wed, 11 Dec 2024   Prob (F-statistic):              0.771\n",
      "Time:                        15:06:33   Log-Likelihood:                 363.13\n",
      "No. Observations:                 348   AIC:                            -722.3\n",
      "Df Residuals:                     346   BIC:                            -714.5\n",
      "Df Model:                           1                                         \n",
      "Covariance Type:                  HAC                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0206      0.004      4.618      0.000       0.012       0.029\n",
      "Raw_return     0.0254      0.087      0.291      0.771      -0.145       0.196\n",
      "==============================================================================\n",
      "Omnibus:                       34.385   Durbin-Watson:                   1.816\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              121.262\n",
      "Skew:                          -0.336   Prob(JB):                     4.66e-27\n",
      "Kurtosis:                       5.812   Cond. No.                         13.1\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors are heteroscedasticity and autocorrelation robust (HAC) using 6 lags and without small sample correction\n"
     ]
    }
   ],
   "source": [
    "# 把投资策略回归到大盘上\n",
    "model_size = smf.ols('My_portfolio ~ Raw_return',data=MYPORT).fit(\n",
    "    cov_type='HAC', cov_kwds={'maxlags': 6}\n",
    ")\n",
    "print(model_size.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$\n",
    "R_{size,t}=0.0206(\\alpha)^{***} + 0.0254 (\\beta) * R_{m,t}\n",
    "$$\n",
    "即0.0206是显著的，0.0254是不显著的\n",
    "\n",
    "小公司风险和大公司风险几乎一样，但收益率明显更高，所以公司规模投资策略明显是$\\alpha$策略"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "理论上的模型\n",
    "$$\n",
    "R_{small,t} - R_{big,t} = \\alpha + (\\beta_{small}-\\beta_{big}) * R_{m,t}\n",
    "$$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 投资策略的Sharpe Ratio\n",
    "\n",
    "$$\n",
    "\\frac{R_{t}}{sd(R_{t})}\n",
    "$$\n",
    "投资组合的平均回报除以其标准差"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8421606208535234"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 投资组合的年化sharpe_ratio\n",
    "sharpe_ratio = MYPORT['My_portfolio'].mean() *12/ (MYPORT['My_portfolio'].std() * np.sqrt(12)) # 用月度求年化\n",
    "sharpe_ratio\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.2942703296344494"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 大盘的年化sharpe_ratio\n",
    "sharpe_ratio = MYPORT['Raw_return'].mean() *12/ (MYPORT['My_portfolio'].std() * np.sqrt(12)) # 用月度求年化\n",
    "sharpe_ratio"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "投资组合的单位风险收益率是大盘的单位风险收益率的3倍左右"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 规模策略价格图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
       "      <th>P5</th>\n",
       "      <th>P6</th>\n",
       "      <th>P7</th>\n",
       "      <th>P8</th>\n",
       "      <th>P9</th>\n",
       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "      <th>Raw_return</th>\n",
       "      <th>price_portfolio</th>\n",
       "      <th>price_small</th>\n",
       "      <th>price_big</th>\n",
       "      <th>price_market</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.145162</td>\n",
       "      <td>-0.133811</td>\n",
       "      <td>-0.131991</td>\n",
       "      <td>-0.141603</td>\n",
       "      <td>-0.138500</td>\n",
       "      <td>-0.129420</td>\n",
       "      <td>-0.125187</td>\n",
       "      <td>-0.133302</td>\n",
       "      <td>-0.142752</td>\n",
       "      <td>-0.131525</td>\n",
       "      <td>-0.013637</td>\n",
       "      <td>-0.131631</td>\n",
       "      <td>0.986363</td>\n",
       "      <td>0.854838</td>\n",
       "      <td>0.868475</td>\n",
       "      <td>0.868369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>-0.014135</td>\n",
       "      <td>-0.016487</td>\n",
       "      <td>-0.026105</td>\n",
       "      <td>-0.013507</td>\n",
       "      <td>-0.027373</td>\n",
       "      <td>-0.031945</td>\n",
       "      <td>-0.013020</td>\n",
       "      <td>-0.020658</td>\n",
       "      <td>-0.028212</td>\n",
       "      <td>-0.030146</td>\n",
       "      <td>0.016012</td>\n",
       "      <td>-0.023694</td>\n",
       "      <td>1.002156</td>\n",
       "      <td>0.842756</td>\n",
       "      <td>0.842294</td>\n",
       "      <td>0.847794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>0.145888</td>\n",
       "      <td>0.124613</td>\n",
       "      <td>0.137706</td>\n",
       "      <td>0.151517</td>\n",
       "      <td>0.172736</td>\n",
       "      <td>0.151145</td>\n",
       "      <td>0.132809</td>\n",
       "      <td>0.102804</td>\n",
       "      <td>0.128072</td>\n",
       "      <td>0.160310</td>\n",
       "      <td>-0.014422</td>\n",
       "      <td>0.177803</td>\n",
       "      <td>0.987703</td>\n",
       "      <td>0.965703</td>\n",
       "      <td>0.977322</td>\n",
       "      <td>0.998534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>-0.129085</td>\n",
       "      <td>-0.117482</td>\n",
       "      <td>-0.104661</td>\n",
       "      <td>-0.114248</td>\n",
       "      <td>-0.100667</td>\n",
       "      <td>-0.092057</td>\n",
       "      <td>-0.118221</td>\n",
       "      <td>-0.123341</td>\n",
       "      <td>-0.095764</td>\n",
       "      <td>-0.112655</td>\n",
       "      <td>-0.016430</td>\n",
       "      <td>-0.103552</td>\n",
       "      <td>0.971475</td>\n",
       "      <td>0.841046</td>\n",
       "      <td>0.867222</td>\n",
       "      <td>0.895133</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.240024</td>\n",
       "      <td>0.178908</td>\n",
       "      <td>0.238830</td>\n",
       "      <td>0.196759</td>\n",
       "      <td>0.179584</td>\n",
       "      <td>0.196451</td>\n",
       "      <td>0.163534</td>\n",
       "      <td>0.179333</td>\n",
       "      <td>0.203274</td>\n",
       "      <td>0.156261</td>\n",
       "      <td>0.083763</td>\n",
       "      <td>0.207922</td>\n",
       "      <td>1.052849</td>\n",
       "      <td>1.042917</td>\n",
       "      <td>1.002735</td>\n",
       "      <td>1.081251</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>0.001526</td>\n",
       "      <td>-0.007487</td>\n",
       "      <td>-0.027998</td>\n",
       "      <td>-0.040304</td>\n",
       "      <td>-0.043932</td>\n",
       "      <td>-0.057348</td>\n",
       "      <td>-0.060162</td>\n",
       "      <td>-0.066902</td>\n",
       "      <td>-0.060407</td>\n",
       "      <td>-0.057794</td>\n",
       "      <td>0.059319</td>\n",
       "      <td>-0.052009</td>\n",
       "      <td>307.840019</td>\n",
       "      <td>1144.563999</td>\n",
       "      <td>2.484129</td>\n",
       "      <td>4.815596</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>0.020277</td>\n",
       "      <td>0.014331</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>-0.009448</td>\n",
       "      <td>-0.003383</td>\n",
       "      <td>0.004828</td>\n",
       "      <td>-0.007206</td>\n",
       "      <td>-0.008534</td>\n",
       "      <td>-0.012221</td>\n",
       "      <td>0.032498</td>\n",
       "      <td>-0.003013</td>\n",
       "      <td>317.844299</td>\n",
       "      <td>1167.772598</td>\n",
       "      <td>2.453770</td>\n",
       "      <td>4.801086</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>0.008199</td>\n",
       "      <td>0.006227</td>\n",
       "      <td>-0.003861</td>\n",
       "      <td>-0.001851</td>\n",
       "      <td>-0.004907</td>\n",
       "      <td>-0.010312</td>\n",
       "      <td>-0.019380</td>\n",
       "      <td>-0.028806</td>\n",
       "      <td>-0.025160</td>\n",
       "      <td>-0.033507</td>\n",
       "      <td>0.041706</td>\n",
       "      <td>-0.029483</td>\n",
       "      <td>331.100158</td>\n",
       "      <td>1177.347059</td>\n",
       "      <td>2.371553</td>\n",
       "      <td>4.659537</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>0.063053</td>\n",
       "      <td>0.058229</td>\n",
       "      <td>0.054380</td>\n",
       "      <td>0.040258</td>\n",
       "      <td>0.050403</td>\n",
       "      <td>0.038414</td>\n",
       "      <td>0.025098</td>\n",
       "      <td>0.013146</td>\n",
       "      <td>0.002612</td>\n",
       "      <td>-0.013457</td>\n",
       "      <td>0.076511</td>\n",
       "      <td>0.003611</td>\n",
       "      <td>356.432852</td>\n",
       "      <td>1251.582727</td>\n",
       "      <td>2.339638</td>\n",
       "      <td>4.676365</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.005808</td>\n",
       "      <td>-0.005787</td>\n",
       "      <td>-0.011312</td>\n",
       "      <td>-0.016412</td>\n",
       "      <td>-0.031357</td>\n",
       "      <td>-0.029353</td>\n",
       "      <td>-0.035430</td>\n",
       "      <td>-0.029991</td>\n",
       "      <td>-0.028759</td>\n",
       "      <td>-0.017816</td>\n",
       "      <td>0.012008</td>\n",
       "      <td>-0.018067</td>\n",
       "      <td>360.713058</td>\n",
       "      <td>1244.313871</td>\n",
       "      <td>2.297955</td>\n",
       "      <td>4.591876</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>348 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1995-01-31 -0.145162 -0.133811 -0.131991 -0.141603 -0.138500 -0.129420   \n",
       "1995-02-28 -0.014135 -0.016487 -0.026105 -0.013507 -0.027373 -0.031945   \n",
       "1995-03-31  0.145888  0.124613  0.137706  0.151517  0.172736  0.151145   \n",
       "1995-04-30 -0.129085 -0.117482 -0.104661 -0.114248 -0.100667 -0.092057   \n",
       "1995-05-31  0.240024  0.178908  0.238830  0.196759  0.179584  0.196451   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31  0.001526 -0.007487 -0.027998 -0.040304 -0.043932 -0.057348   \n",
       "2023-09-30  0.020277  0.014331 -0.000218  0.001945 -0.009448 -0.003383   \n",
       "2023-10-31  0.008199  0.006227 -0.003861 -0.001851 -0.004907 -0.010312   \n",
       "2023-11-30  0.063053  0.058229  0.054380  0.040258  0.050403  0.038414   \n",
       "2023-12-31 -0.005808 -0.005787 -0.011312 -0.016412 -0.031357 -0.029353   \n",
       "\n",
       "                  P7        P8        P9      Pmax  My_portfolio  Raw_return  \\\n",
       "month                                                                          \n",
       "1995-01-31 -0.125187 -0.133302 -0.142752 -0.131525     -0.013637   -0.131631   \n",
       "1995-02-28 -0.013020 -0.020658 -0.028212 -0.030146      0.016012   -0.023694   \n",
       "1995-03-31  0.132809  0.102804  0.128072  0.160310     -0.014422    0.177803   \n",
       "1995-04-30 -0.118221 -0.123341 -0.095764 -0.112655     -0.016430   -0.103552   \n",
       "1995-05-31  0.163534  0.179333  0.203274  0.156261      0.083763    0.207922   \n",
       "...              ...       ...       ...       ...           ...         ...   \n",
       "2023-08-31 -0.060162 -0.066902 -0.060407 -0.057794      0.059319   -0.052009   \n",
       "2023-09-30  0.004828 -0.007206 -0.008534 -0.012221      0.032498   -0.003013   \n",
       "2023-10-31 -0.019380 -0.028806 -0.025160 -0.033507      0.041706   -0.029483   \n",
       "2023-11-30  0.025098  0.013146  0.002612 -0.013457      0.076511    0.003611   \n",
       "2023-12-31 -0.035430 -0.029991 -0.028759 -0.017816      0.012008   -0.018067   \n",
       "\n",
       "            price_portfolio  price_small  price_big  price_market  \n",
       "month                                                              \n",
       "1995-01-31         0.986363     0.854838   0.868475      0.868369  \n",
       "1995-02-28         1.002156     0.842756   0.842294      0.847794  \n",
       "1995-03-31         0.987703     0.965703   0.977322      0.998534  \n",
       "1995-04-30         0.971475     0.841046   0.867222      0.895133  \n",
       "1995-05-31         1.052849     1.042917   1.002735      1.081251  \n",
       "...                     ...          ...        ...           ...  \n",
       "2023-08-31       307.840019  1144.563999   2.484129      4.815596  \n",
       "2023-09-30       317.844299  1167.772598   2.453770      4.801086  \n",
       "2023-10-31       331.100158  1177.347059   2.371553      4.659537  \n",
       "2023-11-30       356.432852  1251.582727   2.339638      4.676365  \n",
       "2023-12-31       360.713058  1244.313871   2.297955      4.591876  \n",
       "\n",
       "[348 rows x 16 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 还原投资策略的价格\n",
    "MYPORT['price_portfolio'] = (1 + MYPORT['My_portfolio']).cumprod()\n",
    "MYPORT['price_small'] = (1 + MYPORT['P1']).cumprod()\n",
    "MYPORT['price_big'] = (1 + MYPORT['Pmax']).cumprod()\n",
    "MYPORT['price_market'] = (1 + MYPORT['Raw_return']).cumprod()\n",
    "MYPORT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
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      ],
      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(16, 6))\n",
    "plt.plot(\n",
    "    'price_portfolio',  \n",
    "    '.-r', \n",
    "    label='Price of My Portfolio',  \n",
    "    linewidth=1, \n",
    "    data=MYPORT)  \n",
    "plt.title(\"China's Stock Market\") \n",
    "plt.xlabel('Month') \n",
    "plt.ylabel('Return') \n",
    "\n",
    "plt.plot(\n",
    "    'price_market', \n",
    "    '.-b', \n",
    "    label='Price of Market', \n",
    "    linewidth=1, \n",
    "    data=MYPORT) \n",
    "\n",
    "plt.plot(\n",
    "    'price_small', \n",
    "    '.-g', \n",
    "    label='Price of Smallest', \n",
    "    linewidth=1, \n",
    "    data=MYPORT) \n",
    "\n",
    "plt.plot(\n",
    "    'price_big', \n",
    "    '.-c', \n",
    "    label='Price of Bigest', \n",
    "    linewidth=1, \n",
    "    data=MYPORT) \n",
    "plt.legend() # 显示图例\n",
    "fig = plt.gcf()\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Drawdown: -0.7518251097331382\n"
     ]
    }
   ],
   "source": [
    "# 计算累积收益率\n",
    "MYPORT['cumulative_return'] = (1 + MYPORT['My_portfolio']).cumprod()\n",
    "\n",
    "# 计算滚动最大值\n",
    "MYPORT['rolling_max'] = MYPORT['cumulative_return'].cummax()\n",
    "\n",
    "# 计算回撤\n",
    "MYPORT['drawdown'] = MYPORT['cumulative_return'] / MYPORT['rolling_max'] - 1\n",
    "\n",
    "# 计算最大回撤\n",
    "max_drawdown = MYPORT['drawdown'].min()\n",
    "print(f\"Maximum Drawdown: {max_drawdown}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Maximum Drawdown: -0.7518251097331382\n",
      "Maximum Drawdown Start Date: 2002-05-31 00:00:00\n",
      "Maximum Drawdown End Date: 2006-12-31 00:00:00\n"
     ]
    }
   ],
   "source": [
    "# 找出最大回撤的时间\n",
    "max_drawdown_end = MYPORT['drawdown'].idxmin() # 返回 Series 中最小值的索引\n",
    "max_drawdown_start = MYPORT.loc[:max_drawdown_end, 'cumulative_return'].idxmax() # 这部分代码选择了从数据开始到 max_drawdown_end 时间点之间的所有累积收益率\n",
    "\n",
    "print(f\"Maximum Drawdown: {max_drawdown}\")\n",
    "print(f\"Maximum Drawdown Start Date: {max_drawdown_start}\")\n",
    "print(f\"Maximum Drawdown End Date: {max_drawdown_end}\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 不同样本"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
       "      <th>P5</th>\n",
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       "      <th>P7</th>\n",
       "      <th>P8</th>\n",
       "      <th>P9</th>\n",
       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "      <th>Raw_return</th>\n",
       "      <th>price_portfolio</th>\n",
       "      <th>price_small</th>\n",
       "      <th>price_big</th>\n",
       "      <th>price_market</th>\n",
       "      <th>cumulative_return</th>\n",
       "      <th>rolling_max</th>\n",
       "      <th>drawdown</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-01-31</th>\n",
       "      <td>-0.145162</td>\n",
       "      <td>-0.133811</td>\n",
       "      <td>-0.131991</td>\n",
       "      <td>-0.141603</td>\n",
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       "      <td>0.868475</td>\n",
       "      <td>0.868369</td>\n",
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       "      <td>0.986363</td>\n",
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       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>-0.014135</td>\n",
       "      <td>-0.016487</td>\n",
       "      <td>-0.026105</td>\n",
       "      <td>-0.013507</td>\n",
       "      <td>-0.027373</td>\n",
       "      <td>-0.031945</td>\n",
       "      <td>-0.013020</td>\n",
       "      <td>-0.020658</td>\n",
       "      <td>-0.028212</td>\n",
       "      <td>-0.030146</td>\n",
       "      <td>0.016012</td>\n",
       "      <td>-0.023694</td>\n",
       "      <td>1.002156</td>\n",
       "      <td>0.842756</td>\n",
       "      <td>0.842294</td>\n",
       "      <td>0.847794</td>\n",
       "      <td>1.002156</td>\n",
       "      <td>1.002156</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>0.145888</td>\n",
       "      <td>0.124613</td>\n",
       "      <td>0.137706</td>\n",
       "      <td>0.151517</td>\n",
       "      <td>0.172736</td>\n",
       "      <td>0.151145</td>\n",
       "      <td>0.132809</td>\n",
       "      <td>0.102804</td>\n",
       "      <td>0.128072</td>\n",
       "      <td>0.160310</td>\n",
       "      <td>-0.014422</td>\n",
       "      <td>0.177803</td>\n",
       "      <td>0.987703</td>\n",
       "      <td>0.965703</td>\n",
       "      <td>0.977322</td>\n",
       "      <td>0.998534</td>\n",
       "      <td>0.987703</td>\n",
       "      <td>1.002156</td>\n",
       "      <td>-0.014422</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>-0.129085</td>\n",
       "      <td>-0.117482</td>\n",
       "      <td>-0.104661</td>\n",
       "      <td>-0.114248</td>\n",
       "      <td>-0.100667</td>\n",
       "      <td>-0.092057</td>\n",
       "      <td>-0.118221</td>\n",
       "      <td>-0.123341</td>\n",
       "      <td>-0.095764</td>\n",
       "      <td>-0.112655</td>\n",
       "      <td>-0.016430</td>\n",
       "      <td>-0.103552</td>\n",
       "      <td>0.971475</td>\n",
       "      <td>0.841046</td>\n",
       "      <td>0.867222</td>\n",
       "      <td>0.895133</td>\n",
       "      <td>0.971475</td>\n",
       "      <td>1.002156</td>\n",
       "      <td>-0.030615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.240024</td>\n",
       "      <td>0.178908</td>\n",
       "      <td>0.238830</td>\n",
       "      <td>0.196759</td>\n",
       "      <td>0.179584</td>\n",
       "      <td>0.196451</td>\n",
       "      <td>0.163534</td>\n",
       "      <td>0.179333</td>\n",
       "      <td>0.203274</td>\n",
       "      <td>0.156261</td>\n",
       "      <td>0.083763</td>\n",
       "      <td>0.207922</td>\n",
       "      <td>1.052849</td>\n",
       "      <td>1.042917</td>\n",
       "      <td>1.002735</td>\n",
       "      <td>1.081251</td>\n",
       "      <td>1.052849</td>\n",
       "      <td>1.052849</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-08-31</th>\n",
       "      <td>-0.211612</td>\n",
       "      <td>-0.227714</td>\n",
       "      <td>-0.229304</td>\n",
       "      <td>-0.233168</td>\n",
       "      <td>-0.224725</td>\n",
       "      <td>-0.241339</td>\n",
       "      <td>-0.245395</td>\n",
       "      <td>-0.242011</td>\n",
       "      <td>-0.231949</td>\n",
       "      <td>-0.126490</td>\n",
       "      <td>-0.085122</td>\n",
       "      <td>-0.136307</td>\n",
       "      <td>6.050851</td>\n",
       "      <td>17.506970</td>\n",
       "      <td>2.160698</td>\n",
       "      <td>3.700387</td>\n",
       "      <td>6.050851</td>\n",
       "      <td>10.206976</td>\n",
       "      <td>-0.407185</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-09-30</th>\n",
       "      <td>-0.122316</td>\n",
       "      <td>-0.107537</td>\n",
       "      <td>-0.092546</td>\n",
       "      <td>-0.101829</td>\n",
       "      <td>-0.105507</td>\n",
       "      <td>-0.084760</td>\n",
       "      <td>-0.089750</td>\n",
       "      <td>-0.065620</td>\n",
       "      <td>-0.042731</td>\n",
       "      <td>-0.042012</td>\n",
       "      <td>-0.080304</td>\n",
       "      <td>-0.043210</td>\n",
       "      <td>5.564942</td>\n",
       "      <td>15.365583</td>\n",
       "      <td>2.069923</td>\n",
       "      <td>3.540494</td>\n",
       "      <td>5.564942</td>\n",
       "      <td>10.206976</td>\n",
       "      <td>-0.454790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-10-31</th>\n",
       "      <td>-0.227984</td>\n",
       "      <td>-0.232990</td>\n",
       "      <td>-0.254290</td>\n",
       "      <td>-0.271172</td>\n",
       "      <td>-0.249400</td>\n",
       "      <td>-0.268830</td>\n",
       "      <td>-0.275560</td>\n",
       "      <td>-0.268572</td>\n",
       "      <td>-0.279455</td>\n",
       "      <td>-0.249162</td>\n",
       "      <td>0.021178</td>\n",
       "      <td>-0.246314</td>\n",
       "      <td>5.682794</td>\n",
       "      <td>11.862469</td>\n",
       "      <td>1.554177</td>\n",
       "      <td>2.668421</td>\n",
       "      <td>5.682794</td>\n",
       "      <td>10.206976</td>\n",
       "      <td>-0.443244</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-11-30</th>\n",
       "      <td>0.232040</td>\n",
       "      <td>0.204959</td>\n",
       "      <td>0.213068</td>\n",
       "      <td>0.217748</td>\n",
       "      <td>0.224971</td>\n",
       "      <td>0.217534</td>\n",
       "      <td>0.179756</td>\n",
       "      <td>0.158848</td>\n",
       "      <td>0.148033</td>\n",
       "      <td>0.073819</td>\n",
       "      <td>0.158221</td>\n",
       "      <td>0.082352</td>\n",
       "      <td>6.581932</td>\n",
       "      <td>14.615039</td>\n",
       "      <td>1.668905</td>\n",
       "      <td>2.888172</td>\n",
       "      <td>6.581932</td>\n",
       "      <td>10.206976</td>\n",
       "      <td>-0.355154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-12-31</th>\n",
       "      <td>0.151222</td>\n",
       "      <td>0.125047</td>\n",
       "      <td>0.095572</td>\n",
       "      <td>0.093324</td>\n",
       "      <td>0.056477</td>\n",
       "      <td>0.066392</td>\n",
       "      <td>0.051165</td>\n",
       "      <td>0.063320</td>\n",
       "      <td>0.037494</td>\n",
       "      <td>-0.040686</td>\n",
       "      <td>0.191908</td>\n",
       "      <td>-0.026908</td>\n",
       "      <td>7.845056</td>\n",
       "      <td>16.825153</td>\n",
       "      <td>1.601004</td>\n",
       "      <td>2.810456</td>\n",
       "      <td>7.845056</td>\n",
       "      <td>10.206976</td>\n",
       "      <td>-0.231403</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>168 rows × 19 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1995-01-31 -0.145162 -0.133811 -0.131991 -0.141603 -0.138500 -0.129420   \n",
       "1995-02-28 -0.014135 -0.016487 -0.026105 -0.013507 -0.027373 -0.031945   \n",
       "1995-03-31  0.145888  0.124613  0.137706  0.151517  0.172736  0.151145   \n",
       "1995-04-30 -0.129085 -0.117482 -0.104661 -0.114248 -0.100667 -0.092057   \n",
       "1995-05-31  0.240024  0.178908  0.238830  0.196759  0.179584  0.196451   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2008-08-31 -0.211612 -0.227714 -0.229304 -0.233168 -0.224725 -0.241339   \n",
       "2008-09-30 -0.122316 -0.107537 -0.092546 -0.101829 -0.105507 -0.084760   \n",
       "2008-10-31 -0.227984 -0.232990 -0.254290 -0.271172 -0.249400 -0.268830   \n",
       "2008-11-30  0.232040  0.204959  0.213068  0.217748  0.224971  0.217534   \n",
       "2008-12-31  0.151222  0.125047  0.095572  0.093324  0.056477  0.066392   \n",
       "\n",
       "                  P7        P8        P9      Pmax  My_portfolio  Raw_return  \\\n",
       "month                                                                          \n",
       "1995-01-31 -0.125187 -0.133302 -0.142752 -0.131525     -0.013637   -0.131631   \n",
       "1995-02-28 -0.013020 -0.020658 -0.028212 -0.030146      0.016012   -0.023694   \n",
       "1995-03-31  0.132809  0.102804  0.128072  0.160310     -0.014422    0.177803   \n",
       "1995-04-30 -0.118221 -0.123341 -0.095764 -0.112655     -0.016430   -0.103552   \n",
       "1995-05-31  0.163534  0.179333  0.203274  0.156261      0.083763    0.207922   \n",
       "...              ...       ...       ...       ...           ...         ...   \n",
       "2008-08-31 -0.245395 -0.242011 -0.231949 -0.126490     -0.085122   -0.136307   \n",
       "2008-09-30 -0.089750 -0.065620 -0.042731 -0.042012     -0.080304   -0.043210   \n",
       "2008-10-31 -0.275560 -0.268572 -0.279455 -0.249162      0.021178   -0.246314   \n",
       "2008-11-30  0.179756  0.158848  0.148033  0.073819      0.158221    0.082352   \n",
       "2008-12-31  0.051165  0.063320  0.037494 -0.040686      0.191908   -0.026908   \n",
       "\n",
       "            price_portfolio  price_small  price_big  price_market  \\\n",
       "month                                                               \n",
       "1995-01-31         0.986363     0.854838   0.868475      0.868369   \n",
       "1995-02-28         1.002156     0.842756   0.842294      0.847794   \n",
       "1995-03-31         0.987703     0.965703   0.977322      0.998534   \n",
       "1995-04-30         0.971475     0.841046   0.867222      0.895133   \n",
       "1995-05-31         1.052849     1.042917   1.002735      1.081251   \n",
       "...                     ...          ...        ...           ...   \n",
       "2008-08-31         6.050851    17.506970   2.160698      3.700387   \n",
       "2008-09-30         5.564942    15.365583   2.069923      3.540494   \n",
       "2008-10-31         5.682794    11.862469   1.554177      2.668421   \n",
       "2008-11-30         6.581932    14.615039   1.668905      2.888172   \n",
       "2008-12-31         7.845056    16.825153   1.601004      2.810456   \n",
       "\n",
       "            cumulative_return  rolling_max  drawdown  \n",
       "month                                                 \n",
       "1995-01-31           0.986363     0.986363  0.000000  \n",
       "1995-02-28           1.002156     1.002156  0.000000  \n",
       "1995-03-31           0.987703     1.002156 -0.014422  \n",
       "1995-04-30           0.971475     1.002156 -0.030615  \n",
       "1995-05-31           1.052849     1.052849  0.000000  \n",
       "...                       ...          ...       ...  \n",
       "2008-08-31           6.050851    10.206976 -0.407185  \n",
       "2008-09-30           5.564942    10.206976 -0.454790  \n",
       "2008-10-31           5.682794    10.206976 -0.443244  \n",
       "2008-11-30           6.581932    10.206976 -0.355154  \n",
       "2008-12-31           7.845056    10.206976 -0.231403  \n",
       "\n",
       "[168 rows x 19 columns]"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 还原投资策略的价格\n",
    "MYPORT_new = MYPORT['1995':'2008'].copy()\n",
    "MYPORT_new['price_portfolio'] = (1 + MYPORT_new['My_portfolio']).cumprod()\n",
    "MYPORT_new['price_small'] = (1 + MYPORT_new['P1']).cumprod()\n",
    "MYPORT_new['price_big'] = (1 + MYPORT_new['Pmax']).cumprod()\n",
    "MYPORT_new['price_market'] = (1 + MYPORT_new['Raw_return']).cumprod()\n",
    "MYPORT_new"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
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      "text/plain": [
       "<Figure size 1600x600 with 1 Axes>"
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "# 相当于把之前那幅图尺度放大\n",
    "fig = plt.figure(figsize=(16, 6))\n",
    "plt.plot(\n",
    "    'price_portfolio',  \n",
    "    '.-r', \n",
    "    label='Price of My Portfolio',  \n",
    "    linewidth=1, \n",
    "    data=MYPORT_new)  \n",
    "plt.title(\"China's Stock Market\") \n",
    "plt.xlabel('Month') \n",
    "plt.ylabel('Return') \n",
    "\n",
    "plt.plot(\n",
    "    'price_market', \n",
    "    '.-b', \n",
    "    label='Price of Market', \n",
    "    linewidth=1, \n",
    "    data=MYPORT_new) \n",
    "\n",
    "plt.plot(\n",
    "    'price_small', \n",
    "    '.-g', \n",
    "    label='Price of Smallest', \n",
    "    linewidth=1, \n",
    "    data=MYPORT_new) \n",
    "\n",
    "plt.plot(\n",
    "    'price_big', \n",
    "    '.-c', \n",
    "    label='Price of Bigest', \n",
    "    linewidth=1, \n",
    "    data=MYPORT_new) \n",
    "plt.legend() # 显示图例\n",
    "fig = plt.gcf()\n",
    "plt.show();"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 1月效应"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sort</th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
       "      <th>P5</th>\n",
       "      <th>P6</th>\n",
       "      <th>P7</th>\n",
       "      <th>P8</th>\n",
       "      <th>P9</th>\n",
       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "      <th>yue</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1995-02-28</th>\n",
       "      <td>-0.014135</td>\n",
       "      <td>-0.016487</td>\n",
       "      <td>-0.026105</td>\n",
       "      <td>-0.013507</td>\n",
       "      <td>-0.027373</td>\n",
       "      <td>-0.031945</td>\n",
       "      <td>-0.013020</td>\n",
       "      <td>-0.020658</td>\n",
       "      <td>-0.028212</td>\n",
       "      <td>-0.030146</td>\n",
       "      <td>0.016012</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-03-31</th>\n",
       "      <td>0.145888</td>\n",
       "      <td>0.124613</td>\n",
       "      <td>0.137706</td>\n",
       "      <td>0.151517</td>\n",
       "      <td>0.172736</td>\n",
       "      <td>0.151145</td>\n",
       "      <td>0.132809</td>\n",
       "      <td>0.102804</td>\n",
       "      <td>0.128072</td>\n",
       "      <td>0.160310</td>\n",
       "      <td>-0.014422</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-04-30</th>\n",
       "      <td>-0.129085</td>\n",
       "      <td>-0.117482</td>\n",
       "      <td>-0.104661</td>\n",
       "      <td>-0.114248</td>\n",
       "      <td>-0.100667</td>\n",
       "      <td>-0.092057</td>\n",
       "      <td>-0.118221</td>\n",
       "      <td>-0.123341</td>\n",
       "      <td>-0.095764</td>\n",
       "      <td>-0.112655</td>\n",
       "      <td>-0.016430</td>\n",
       "      <td>4</td>\n",
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       "    <tr>\n",
       "      <th>1995-05-31</th>\n",
       "      <td>0.240024</td>\n",
       "      <td>0.178908</td>\n",
       "      <td>0.238830</td>\n",
       "      <td>0.196759</td>\n",
       "      <td>0.179584</td>\n",
       "      <td>0.196451</td>\n",
       "      <td>0.163534</td>\n",
       "      <td>0.179333</td>\n",
       "      <td>0.203274</td>\n",
       "      <td>0.156261</td>\n",
       "      <td>0.083763</td>\n",
       "      <td>5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1995-06-30</th>\n",
       "      <td>-0.024436</td>\n",
       "      <td>-0.073405</td>\n",
       "      <td>-0.079738</td>\n",
       "      <td>-0.106261</td>\n",
       "      <td>-0.089520</td>\n",
       "      <td>-0.109416</td>\n",
       "      <td>-0.104477</td>\n",
       "      <td>-0.104306</td>\n",
       "      <td>-0.123102</td>\n",
       "      <td>-0.100064</td>\n",
       "      <td>0.075628</td>\n",
       "      <td>6</td>\n",
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       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>0.001526</td>\n",
       "      <td>-0.007487</td>\n",
       "      <td>-0.027998</td>\n",
       "      <td>-0.040304</td>\n",
       "      <td>-0.043932</td>\n",
       "      <td>-0.057348</td>\n",
       "      <td>-0.060162</td>\n",
       "      <td>-0.066902</td>\n",
       "      <td>-0.060407</td>\n",
       "      <td>-0.057794</td>\n",
       "      <td>0.059319</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>0.020277</td>\n",
       "      <td>0.014331</td>\n",
       "      <td>-0.000218</td>\n",
       "      <td>0.001945</td>\n",
       "      <td>-0.009448</td>\n",
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       "      <td>-0.008534</td>\n",
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       "      <td>0.032498</td>\n",
       "      <td>9</td>\n",
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       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>0.008199</td>\n",
       "      <td>0.006227</td>\n",
       "      <td>-0.003861</td>\n",
       "      <td>-0.001851</td>\n",
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       "      <td>-0.028806</td>\n",
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       "      <td>0.041706</td>\n",
       "      <td>10</td>\n",
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       "      <th>2023-11-30</th>\n",
       "      <td>0.063053</td>\n",
       "      <td>0.058229</td>\n",
       "      <td>0.054380</td>\n",
       "      <td>0.040258</td>\n",
       "      <td>0.050403</td>\n",
       "      <td>0.038414</td>\n",
       "      <td>0.025098</td>\n",
       "      <td>0.013146</td>\n",
       "      <td>0.002612</td>\n",
       "      <td>-0.013457</td>\n",
       "      <td>0.076511</td>\n",
       "      <td>11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.005808</td>\n",
       "      <td>-0.005787</td>\n",
       "      <td>-0.011312</td>\n",
       "      <td>-0.016412</td>\n",
       "      <td>-0.031357</td>\n",
       "      <td>-0.029353</td>\n",
       "      <td>-0.035430</td>\n",
       "      <td>-0.029991</td>\n",
       "      <td>-0.028759</td>\n",
       "      <td>-0.017816</td>\n",
       "      <td>0.012008</td>\n",
       "      <td>12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>319 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sort              P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1995-02-28 -0.014135 -0.016487 -0.026105 -0.013507 -0.027373 -0.031945   \n",
       "1995-03-31  0.145888  0.124613  0.137706  0.151517  0.172736  0.151145   \n",
       "1995-04-30 -0.129085 -0.117482 -0.104661 -0.114248 -0.100667 -0.092057   \n",
       "1995-05-31  0.240024  0.178908  0.238830  0.196759  0.179584  0.196451   \n",
       "1995-06-30 -0.024436 -0.073405 -0.079738 -0.106261 -0.089520 -0.109416   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31  0.001526 -0.007487 -0.027998 -0.040304 -0.043932 -0.057348   \n",
       "2023-09-30  0.020277  0.014331 -0.000218  0.001945 -0.009448 -0.003383   \n",
       "2023-10-31  0.008199  0.006227 -0.003861 -0.001851 -0.004907 -0.010312   \n",
       "2023-11-30  0.063053  0.058229  0.054380  0.040258  0.050403  0.038414   \n",
       "2023-12-31 -0.005808 -0.005787 -0.011312 -0.016412 -0.031357 -0.029353   \n",
       "\n",
       "sort              P7        P8        P9      Pmax  My_portfolio  yue  \n",
       "month                                                                  \n",
       "1995-02-28 -0.013020 -0.020658 -0.028212 -0.030146      0.016012    2  \n",
       "1995-03-31  0.132809  0.102804  0.128072  0.160310     -0.014422    3  \n",
       "1995-04-30 -0.118221 -0.123341 -0.095764 -0.112655     -0.016430    4  \n",
       "1995-05-31  0.163534  0.179333  0.203274  0.156261      0.083763    5  \n",
       "1995-06-30 -0.104477 -0.104306 -0.123102 -0.100064      0.075628    6  \n",
       "...              ...       ...       ...       ...           ...  ...  \n",
       "2023-08-31 -0.060162 -0.066902 -0.060407 -0.057794      0.059319    8  \n",
       "2023-09-30  0.004828 -0.007206 -0.008534 -0.012221      0.032498    9  \n",
       "2023-10-31 -0.019380 -0.028806 -0.025160 -0.033507      0.041706   10  \n",
       "2023-11-30  0.025098  0.013146  0.002612 -0.013457      0.076511   11  \n",
       "2023-12-31 -0.035430 -0.029991 -0.028759 -0.017816      0.012008   12  \n",
       "\n",
       "[319 rows x 12 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_size_Jan = portfolio_size.copy()# 在数据里生成一列月份\n",
    "portfolio_size_Jan = portfolio_size_Jan.reset_index()# 去索引\n",
    "portfolio_size_Jan['yue'] = portfolio_size_Jan['month'].dt.month# 提取出月份\n",
    "portfolio_size_Jan = portfolio_size_Jan[portfolio_size_Jan['yue'] != 1]# 筛选\n",
    "portfolio_size_Jan.set_index(['month'],inplace=True)# 索引\n",
    "portfolio_size_Jan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:           My_portfolio   R-squared:                       0.000\n",
      "Model:                            OLS   Adj. R-squared:                  0.000\n",
      "Method:                 Least Squares   F-statistic:                       nan\n",
      "Date:                Wed, 11 Dec 2024   Prob (F-statistic):                nan\n",
      "Time:                        16:04:44   Log-Likelihood:                 330.88\n",
      "No. Observations:                 319   AIC:                            -659.8\n",
      "Df Residuals:                     318   BIC:                            -656.0\n",
      "Df Model:                           0                                         \n",
      "Covariance Type:                  HAC                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0220      0.005      4.660      0.000       0.013       0.031\n",
      "==============================================================================\n",
      "Omnibus:                       32.779   Durbin-Watson:                   1.905\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):              117.260\n",
      "Skew:                          -0.340   Prob(JB):                     3.45e-26\n",
      "Kurtosis:                       5.891   Cond. No.                         1.00\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors are heteroscedasticity and autocorrelation robust (HAC) using 6 lags and without small sample correction\n"
     ]
    }
   ],
   "source": [
    "# 看一下是否还有效\n",
    "model_size_Jan = smf.ols('My_portfolio ~ 1',data=portfolio_size_Jan).fit(\n",
    "    cov_type='HAC', cov_kwds={'maxlags': 6}\n",
    "    )\n",
    "print(model_size_Jan.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "说明没了1月还是有效"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Value 策略"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Stkcd</th>\n",
       "      <th>month</th>\n",
       "      <th>ep</th>\n",
       "      <th>ep_recent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-04-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-05-31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-06-30</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-07-31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-08-31</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752023</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>0.054878</td>\n",
       "      <td>0.036802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752024</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>0.051179</td>\n",
       "      <td>0.034322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752025</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>0.058164</td>\n",
       "      <td>0.050524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752026</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>0.059760</td>\n",
       "      <td>0.051910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>752027</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>0.054101</td>\n",
       "      <td>0.046995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>752028 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Stkcd      month        ep  ep_recent\n",
       "0       000001 1991-04-30       NaN        NaN\n",
       "1       000001 1991-05-31       NaN        NaN\n",
       "2       000001 1991-06-30       NaN        NaN\n",
       "3       000001 1991-07-31       NaN        NaN\n",
       "4       000001 1991-08-31       NaN        NaN\n",
       "...        ...        ...       ...        ...\n",
       "752023  605599 2023-08-31  0.054878   0.036802\n",
       "752024  605599 2023-09-30  0.051179   0.034322\n",
       "752025  605599 2023-10-31  0.058164   0.050524\n",
       "752026  605599 2023-11-30  0.059760   0.051910\n",
       "752027  605599 2023-12-31  0.054101   0.046995\n",
       "\n",
       "[752028 rows x 4 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "EP = pd.read_csv(\"D:/python-homework/python-homework/EP2023.csv\")\n",
    "EP['month'] = pd.to_datetime(EP['month'], format='%Y-%m-%d') + MonthEnd(1)\n",
    "EP = EP[['Stkcd','month','ep','ep_recent']]# ep是往前推4个季度，ep_recent是最近的\n",
    "EP['Stkcd'] = EP['Stkcd'].apply(lambda x: '{:0>6}'.format(x)) # 6位股票代码\n",
    "EP"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Stkcd</th>\n",
       "      <th>month</th>\n",
       "      <th>price</th>\n",
       "      <th>Rank</th>\n",
       "      <th>Freq</th>\n",
       "      <th>floatingvalue</th>\n",
       "      <th>totalvalue</th>\n",
       "      <th>sizef</th>\n",
       "      <th>sizet</th>\n",
       "      <th>Return</th>\n",
       "      <th>rfmonth</th>\n",
       "      <th>ret</th>\n",
       "      <th>next_ret</th>\n",
       "      <th>w</th>\n",
       "      <th>ep</th>\n",
       "      <th>ep_recent</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-05-31</td>\n",
       "      <td>38.34</td>\n",
       "      <td>2</td>\n",
       "      <td>24.0</td>\n",
       "      <td>1.016010e+09</td>\n",
       "      <td>1.859497e+09</td>\n",
       "      <td>20.739149</td>\n",
       "      <td>21.343572</td>\n",
       "      <td>-0.122253</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.128345</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-06-30</td>\n",
       "      <td>33.99</td>\n",
       "      <td>3</td>\n",
       "      <td>23.0</td>\n",
       "      <td>9.007350e+08</td>\n",
       "      <td>1.648521e+09</td>\n",
       "      <td>20.618722</td>\n",
       "      <td>21.223144</td>\n",
       "      <td>-0.113459</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.119551</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-07-31</td>\n",
       "      <td>29.54</td>\n",
       "      <td>4</td>\n",
       "      <td>16.0</td>\n",
       "      <td>7.828100e+08</td>\n",
       "      <td>1.432695e+09</td>\n",
       "      <td>20.478401</td>\n",
       "      <td>21.082823</td>\n",
       "      <td>-0.130921</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.137013</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-08-31</td>\n",
       "      <td>15.00</td>\n",
       "      <td>5</td>\n",
       "      <td>15.0</td>\n",
       "      <td>6.748338e+08</td>\n",
       "      <td>1.346275e+09</td>\n",
       "      <td>20.329977</td>\n",
       "      <td>21.020607</td>\n",
       "      <td>-0.411588</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.417680</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>000001</td>\n",
       "      <td>1991-09-30</td>\n",
       "      <td>14.50</td>\n",
       "      <td>6</td>\n",
       "      <td>24.0</td>\n",
       "      <td>6.523394e+08</td>\n",
       "      <td>1.301399e+09</td>\n",
       "      <td>20.296075</td>\n",
       "      <td>20.986706</td>\n",
       "      <td>-0.033333</td>\n",
       "      <td>0.006092</td>\n",
       "      <td>-0.039425</td>\n",
       "      <td>0.849080</td>\n",
       "      <td>1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709878</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>13.56</td>\n",
       "      <td>24</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.955351e+09</td>\n",
       "      <td>1.054667e+10</td>\n",
       "      <td>22.797111</td>\n",
       "      <td>23.079076</td>\n",
       "      <td>-0.025862</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>1</td>\n",
       "      <td>0.054878</td>\n",
       "      <td>0.036802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709879</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>14.54</td>\n",
       "      <td>25</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.530295e+09</td>\n",
       "      <td>1.130889e+10</td>\n",
       "      <td>22.866890</td>\n",
       "      <td>23.148855</td>\n",
       "      <td>0.072271</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>1</td>\n",
       "      <td>0.051179</td>\n",
       "      <td>0.034322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709880</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>13.85</td>\n",
       "      <td>26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.125488e+09</td>\n",
       "      <td>1.077222e+10</td>\n",
       "      <td>22.818272</td>\n",
       "      <td>23.100237</td>\n",
       "      <td>-0.047455</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>1</td>\n",
       "      <td>0.058164</td>\n",
       "      <td>0.050524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709881</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>13.48</td>\n",
       "      <td>27</td>\n",
       "      <td>22.0</td>\n",
       "      <td>7.908417e+09</td>\n",
       "      <td>1.048444e+10</td>\n",
       "      <td>22.791193</td>\n",
       "      <td>23.073159</td>\n",
       "      <td>-0.026715</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>1</td>\n",
       "      <td>0.059760</td>\n",
       "      <td>0.051910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709882</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>14.89</td>\n",
       "      <td>28</td>\n",
       "      <td>21.0</td>\n",
       "      <td>8.735632e+09</td>\n",
       "      <td>1.158111e+10</td>\n",
       "      <td>22.890676</td>\n",
       "      <td>23.172641</td>\n",
       "      <td>0.104599</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1</td>\n",
       "      <td>0.054101</td>\n",
       "      <td>0.046995</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>709883 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Stkcd      month  price  Rank  Freq  floatingvalue    totalvalue  \\\n",
       "0       000001 1991-05-31  38.34     2  24.0   1.016010e+09  1.859497e+09   \n",
       "1       000001 1991-06-30  33.99     3  23.0   9.007350e+08  1.648521e+09   \n",
       "2       000001 1991-07-31  29.54     4  16.0   7.828100e+08  1.432695e+09   \n",
       "3       000001 1991-08-31  15.00     5  15.0   6.748338e+08  1.346275e+09   \n",
       "4       000001 1991-09-30  14.50     6  24.0   6.523394e+08  1.301399e+09   \n",
       "...        ...        ...    ...   ...   ...            ...           ...   \n",
       "709878  605599 2023-08-31  13.56    24  23.0   7.955351e+09  1.054667e+10   \n",
       "709879  605599 2023-09-30  14.54    25  20.0   8.530295e+09  1.130889e+10   \n",
       "709880  605599 2023-10-31  13.85    26  17.0   8.125488e+09  1.077222e+10   \n",
       "709881  605599 2023-11-30  13.48    27  22.0   7.908417e+09  1.048444e+10   \n",
       "709882  605599 2023-12-31  14.89    28  21.0   8.735632e+09  1.158111e+10   \n",
       "\n",
       "            sizef      sizet    Return   rfmonth       ret  next_ret  w  \\\n",
       "0       20.739149  21.343572 -0.122253  0.006092 -0.128345 -0.119551  1   \n",
       "1       20.618722  21.223144 -0.113459  0.006092 -0.119551 -0.137013  1   \n",
       "2       20.478401  21.082823 -0.130921  0.006092 -0.137013 -0.417680  1   \n",
       "3       20.329977  21.020607 -0.411588  0.006092 -0.417680 -0.039425  1   \n",
       "4       20.296075  20.986706 -0.033333  0.006092 -0.039425  0.849080  1   \n",
       "...           ...        ...       ...       ...       ...       ... ..   \n",
       "709878  22.797111  23.079076 -0.025862  0.001241 -0.027103  0.071030  1   \n",
       "709879  22.866890  23.148855  0.072271  0.001241  0.071030 -0.048696  1   \n",
       "709880  22.818272  23.100237 -0.047455  0.001241 -0.048696 -0.027956  1   \n",
       "709881  22.791193  23.073159 -0.026715  0.001241 -0.027956  0.103358  1   \n",
       "709882  22.890676  23.172641  0.104599  0.001241  0.103358       NaN  1   \n",
       "\n",
       "              ep  ep_recent  \n",
       "0            NaN        NaN  \n",
       "1            NaN        NaN  \n",
       "2            NaN        NaN  \n",
       "3            NaN        NaN  \n",
       "4            NaN        NaN  \n",
       "...          ...        ...  \n",
       "709878  0.054878   0.036802  \n",
       "709879  0.051179   0.034322  \n",
       "709880  0.058164   0.050524  \n",
       "709881  0.059760   0.051910  \n",
       "709882  0.054101   0.046995  \n",
       "\n",
       "[709883 rows x 16 columns]"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "cross = pd.merge(cross,EP[['Stkcd','month','ep','ep_recent']],on=['Stkcd','month'],how='left')\n",
    "cross"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "EP高 回报率高"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>one</th>\n",
       "      <th>two</th>\n",
       "      <th>three</th>\n",
       "      <th>four</th>\n",
       "      <th>five</th>\n",
       "      <th>six</th>\n",
       "      <th>seven</th>\n",
       "      <th>eight</th>\n",
       "      <th>nine</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1991-01-31</th>\n",
       "      <td>0.002956</td>\n",
       "      <td>0.003836</td>\n",
       "      <td>0.004363</td>\n",
       "      <td>0.004537</td>\n",
       "      <td>0.004711</td>\n",
       "      <td>0.011987</td>\n",
       "      <td>0.019263</td>\n",
       "      <td>0.025699</td>\n",
       "      <td>0.031296</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-02-28</th>\n",
       "      <td>0.002958</td>\n",
       "      <td>0.003930</td>\n",
       "      <td>0.004309</td>\n",
       "      <td>0.004688</td>\n",
       "      <td>0.004966</td>\n",
       "      <td>0.005244</td>\n",
       "      <td>0.013876</td>\n",
       "      <td>0.022509</td>\n",
       "      <td>0.030363</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-03-31</th>\n",
       "      <td>0.004372</td>\n",
       "      <td>0.004548</td>\n",
       "      <td>0.005040</td>\n",
       "      <td>0.005532</td>\n",
       "      <td>0.007924</td>\n",
       "      <td>0.010316</td>\n",
       "      <td>0.017923</td>\n",
       "      <td>0.025530</td>\n",
       "      <td>0.033141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-04-30</th>\n",
       "      <td>0.004420</td>\n",
       "      <td>0.004804</td>\n",
       "      <td>0.004970</td>\n",
       "      <td>0.005136</td>\n",
       "      <td>0.008243</td>\n",
       "      <td>0.011350</td>\n",
       "      <td>0.019414</td>\n",
       "      <td>0.027477</td>\n",
       "      <td>0.033992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-05-31</th>\n",
       "      <td>0.004025</td>\n",
       "      <td>0.004807</td>\n",
       "      <td>0.004823</td>\n",
       "      <td>0.004839</td>\n",
       "      <td>0.008903</td>\n",
       "      <td>0.012968</td>\n",
       "      <td>0.020588</td>\n",
       "      <td>0.028207</td>\n",
       "      <td>0.032740</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>-0.049601</td>\n",
       "      <td>-0.011916</td>\n",
       "      <td>0.002636</td>\n",
       "      <td>0.011005</td>\n",
       "      <td>0.018754</td>\n",
       "      <td>0.026098</td>\n",
       "      <td>0.034812</td>\n",
       "      <td>0.047238</td>\n",
       "      <td>0.071377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>-0.048772</td>\n",
       "      <td>-0.012110</td>\n",
       "      <td>0.002575</td>\n",
       "      <td>0.010991</td>\n",
       "      <td>0.018855</td>\n",
       "      <td>0.026206</td>\n",
       "      <td>0.034760</td>\n",
       "      <td>0.047755</td>\n",
       "      <td>0.071173</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>-0.045980</td>\n",
       "      <td>-0.012401</td>\n",
       "      <td>0.001387</td>\n",
       "      <td>0.010373</td>\n",
       "      <td>0.018743</td>\n",
       "      <td>0.026326</td>\n",
       "      <td>0.035554</td>\n",
       "      <td>0.048309</td>\n",
       "      <td>0.071581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>-0.044384</td>\n",
       "      <td>-0.011665</td>\n",
       "      <td>0.001407</td>\n",
       "      <td>0.010007</td>\n",
       "      <td>0.017726</td>\n",
       "      <td>0.025517</td>\n",
       "      <td>0.034661</td>\n",
       "      <td>0.047224</td>\n",
       "      <td>0.070970</td>\n",
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       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.046449</td>\n",
       "      <td>-0.012227</td>\n",
       "      <td>0.001403</td>\n",
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       "      <td>0.018201</td>\n",
       "      <td>0.026014</td>\n",
       "      <td>0.035107</td>\n",
       "      <td>0.048618</td>\n",
       "      <td>0.072682</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>396 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 one       two     three      four      five       six  \\\n",
       "month                                                                    \n",
       "1991-01-31  0.002956  0.003836  0.004363  0.004537  0.004711  0.011987   \n",
       "1991-02-28  0.002958  0.003930  0.004309  0.004688  0.004966  0.005244   \n",
       "1991-03-31  0.004372  0.004548  0.005040  0.005532  0.007924  0.010316   \n",
       "1991-04-30  0.004420  0.004804  0.004970  0.005136  0.008243  0.011350   \n",
       "1991-05-31  0.004025  0.004807  0.004823  0.004839  0.008903  0.012968   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31 -0.049601 -0.011916  0.002636  0.011005  0.018754  0.026098   \n",
       "2023-09-30 -0.048772 -0.012110  0.002575  0.010991  0.018855  0.026206   \n",
       "2023-10-31 -0.045980 -0.012401  0.001387  0.010373  0.018743  0.026326   \n",
       "2023-11-30 -0.044384 -0.011665  0.001407  0.010007  0.017726  0.025517   \n",
       "2023-12-31 -0.046449 -0.012227  0.001403  0.010295  0.018201  0.026014   \n",
       "\n",
       "               seven     eight      nine  \n",
       "month                                     \n",
       "1991-01-31  0.019263  0.025699  0.031296  \n",
       "1991-02-28  0.013876  0.022509  0.030363  \n",
       "1991-03-31  0.017923  0.025530  0.033141  \n",
       "1991-04-30  0.019414  0.027477  0.033992  \n",
       "1991-05-31  0.020588  0.028207  0.032740  \n",
       "...              ...       ...       ...  \n",
       "2023-08-31  0.034812  0.047238  0.071377  \n",
       "2023-09-30  0.034760  0.047755  0.071173  \n",
       "2023-10-31  0.035554  0.048309  0.071581  \n",
       "2023-11-30  0.034661  0.047224  0.070970  \n",
       "2023-12-31  0.035107  0.048618  0.072682  \n",
       "\n",
       "[396 rows x 9 columns]"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fenweishu = pd.DataFrame(\n",
    "    cross.groupby(['month'])['ep'].quantile([0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]))# 把ep分组\n",
    "fenweishu = fenweishu.reset_index()# 去索引\n",
    "fenweishu = fenweishu.pivot_table(index='month',columns='level_1',values='ep')# 数据长变宽\n",
    "fenweishu.columns = ['one','two','three','four','five','six','seven','eight','nine']# 改名\n",
    "fenweishu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
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       "      <th></th>\n",
       "      <th>Stkcd</th>\n",
       "      <th>month</th>\n",
       "      <th>price</th>\n",
       "      <th>Rank</th>\n",
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       "      <th>ep</th>\n",
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       "      <th>two</th>\n",
       "      <th>three</th>\n",
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       "      <th>five</th>\n",
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       "  </thead>\n",
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       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>000001</td>\n",
       "      <td>1994-03-31</td>\n",
       "      <td>15.05</td>\n",
       "      <td>36</td>\n",
       "      <td>23.0</td>\n",
       "      <td>2.184334e+09</td>\n",
       "      <td>4.054739e+09</td>\n",
       "      <td>21.504577</td>\n",
       "      <td>22.123152</td>\n",
       "      <td>-0.170799</td>\n",
       "      <td>0.008719</td>\n",
       "      <td>-0.179518</td>\n",
       "      <td>0.053739</td>\n",
       "      <td>1</td>\n",
       "      <td>0.067405</td>\n",
       "      <td>0.067405</td>\n",
       "      <td>0.001488</td>\n",
       "      <td>0.002004</td>\n",
       "      <td>0.007389</td>\n",
       "      <td>0.013628</td>\n",
       "      <td>0.015989</td>\n",
       "      <td>0.021007</td>\n",
       "      <td>0.026544</td>\n",
       "      <td>0.042954</td>\n",
       "      <td>0.064559</td>\n",
       "      <td>Pmax</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>000001</td>\n",
       "      <td>1994-04-30</td>\n",
       "      <td>15.99</td>\n",
       "      <td>37</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2.320765e+09</td>\n",
       "      <td>4.307992e+09</td>\n",
       "      <td>21.565163</td>\n",
       "      <td>22.183738</td>\n",
       "      <td>0.062458</td>\n",
       "      <td>0.008719</td>\n",
       "      <td>0.053739</td>\n",
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       "      <td>1</td>\n",
       "      <td>0.063443</td>\n",
       "      <td>0.063443</td>\n",
       "      <td>0.002280</td>\n",
       "      <td>0.013236</td>\n",
       "      <td>0.019516</td>\n",
       "      <td>0.027554</td>\n",
       "      <td>0.041036</td>\n",
       "      <td>0.052489</td>\n",
       "      <td>0.062144</td>\n",
       "      <td>0.078678</td>\n",
       "      <td>0.084647</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>000001</td>\n",
       "      <td>1994-05-31</td>\n",
       "      <td>14.60</td>\n",
       "      <td>38</td>\n",
       "      <td>21.0</td>\n",
       "      <td>2.119022e+09</td>\n",
       "      <td>3.933501e+09</td>\n",
       "      <td>21.474221</td>\n",
       "      <td>22.092796</td>\n",
       "      <td>-0.086929</td>\n",
       "      <td>0.008719</td>\n",
       "      <td>-0.095648</td>\n",
       "      <td>-0.088171</td>\n",
       "      <td>1</td>\n",
       "      <td>0.069483</td>\n",
       "      <td>0.069483</td>\n",
       "      <td>0.002379</td>\n",
       "      <td>0.015358</td>\n",
       "      <td>0.024298</td>\n",
       "      <td>0.037559</td>\n",
       "      <td>0.051864</td>\n",
       "      <td>0.059018</td>\n",
       "      <td>0.069656</td>\n",
       "      <td>0.076781</td>\n",
       "      <td>0.089289</td>\n",
       "      <td>P7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>000001</td>\n",
       "      <td>1994-06-30</td>\n",
       "      <td>13.44</td>\n",
       "      <td>39</td>\n",
       "      <td>22.0</td>\n",
       "      <td>2.407403e+09</td>\n",
       "      <td>3.620977e+09</td>\n",
       "      <td>21.601814</td>\n",
       "      <td>22.010010</td>\n",
       "      <td>-0.079452</td>\n",
       "      <td>0.008719</td>\n",
       "      <td>-0.088171</td>\n",
       "      <td>-0.056046</td>\n",
       "      <td>1</td>\n",
       "      <td>0.075480</td>\n",
       "      <td>0.075480</td>\n",
       "      <td>0.002832</td>\n",
       "      <td>0.018418</td>\n",
       "      <td>0.027670</td>\n",
       "      <td>0.049931</td>\n",
       "      <td>0.061135</td>\n",
       "      <td>0.074077</td>\n",
       "      <td>0.086381</td>\n",
       "      <td>0.090049</td>\n",
       "      <td>0.114688</td>\n",
       "      <td>P7</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>000001</td>\n",
       "      <td>1994-07-31</td>\n",
       "      <td>8.00</td>\n",
       "      <td>40</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2.292765e+09</td>\n",
       "      <td>3.448549e+09</td>\n",
       "      <td>21.553024</td>\n",
       "      <td>21.961219</td>\n",
       "      <td>-0.047327</td>\n",
       "      <td>0.008719</td>\n",
       "      <td>-0.056046</td>\n",
       "      <td>0.553781</td>\n",
       "      <td>1</td>\n",
       "      <td>0.079254</td>\n",
       "      <td>0.079254</td>\n",
       "      <td>0.004204</td>\n",
       "      <td>0.027413</td>\n",
       "      <td>0.035091</td>\n",
       "      <td>0.061044</td>\n",
       "      <td>0.075252</td>\n",
       "      <td>0.087968</td>\n",
       "      <td>0.101297</td>\n",
       "      <td>0.123165</td>\n",
       "      <td>0.142412</td>\n",
       "      <td>P6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709877</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-07-31</td>\n",
       "      <td>13.92</td>\n",
       "      <td>23</td>\n",
       "      <td>21.0</td>\n",
       "      <td>8.166555e+09</td>\n",
       "      <td>1.082667e+10</td>\n",
       "      <td>22.823313</td>\n",
       "      <td>23.105278</td>\n",
       "      <td>0.053747</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.052506</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>1</td>\n",
       "      <td>0.041298</td>\n",
       "      <td>0.019832</td>\n",
       "      <td>-0.046221</td>\n",
       "      <td>-0.010509</td>\n",
       "      <td>0.003185</td>\n",
       "      <td>0.011029</td>\n",
       "      <td>0.018120</td>\n",
       "      <td>0.025115</td>\n",
       "      <td>0.033761</td>\n",
       "      <td>0.044528</td>\n",
       "      <td>0.069779</td>\n",
       "      <td>P8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709878</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-08-31</td>\n",
       "      <td>13.56</td>\n",
       "      <td>24</td>\n",
       "      <td>23.0</td>\n",
       "      <td>7.955351e+09</td>\n",
       "      <td>1.054667e+10</td>\n",
       "      <td>22.797111</td>\n",
       "      <td>23.079076</td>\n",
       "      <td>-0.025862</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027103</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>1</td>\n",
       "      <td>0.054878</td>\n",
       "      <td>0.036802</td>\n",
       "      <td>-0.049601</td>\n",
       "      <td>-0.011916</td>\n",
       "      <td>0.002636</td>\n",
       "      <td>0.011005</td>\n",
       "      <td>0.018754</td>\n",
       "      <td>0.026098</td>\n",
       "      <td>0.034812</td>\n",
       "      <td>0.047238</td>\n",
       "      <td>0.071377</td>\n",
       "      <td>P9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709879</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-09-30</td>\n",
       "      <td>14.54</td>\n",
       "      <td>25</td>\n",
       "      <td>20.0</td>\n",
       "      <td>8.530295e+09</td>\n",
       "      <td>1.130889e+10</td>\n",
       "      <td>22.866890</td>\n",
       "      <td>23.148855</td>\n",
       "      <td>0.072271</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>0.071030</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>1</td>\n",
       "      <td>0.051179</td>\n",
       "      <td>0.034322</td>\n",
       "      <td>-0.048772</td>\n",
       "      <td>-0.012110</td>\n",
       "      <td>0.002575</td>\n",
       "      <td>0.010991</td>\n",
       "      <td>0.018855</td>\n",
       "      <td>0.026206</td>\n",
       "      <td>0.034760</td>\n",
       "      <td>0.047755</td>\n",
       "      <td>0.071173</td>\n",
       "      <td>P9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709880</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-10-31</td>\n",
       "      <td>13.85</td>\n",
       "      <td>26</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8.125488e+09</td>\n",
       "      <td>1.077222e+10</td>\n",
       "      <td>22.818272</td>\n",
       "      <td>23.100237</td>\n",
       "      <td>-0.047455</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.048696</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>1</td>\n",
       "      <td>0.058164</td>\n",
       "      <td>0.050524</td>\n",
       "      <td>-0.045980</td>\n",
       "      <td>-0.012401</td>\n",
       "      <td>0.001387</td>\n",
       "      <td>0.010373</td>\n",
       "      <td>0.018743</td>\n",
       "      <td>0.026326</td>\n",
       "      <td>0.035554</td>\n",
       "      <td>0.048309</td>\n",
       "      <td>0.071581</td>\n",
       "      <td>P9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>709881</th>\n",
       "      <td>605599</td>\n",
       "      <td>2023-11-30</td>\n",
       "      <td>13.48</td>\n",
       "      <td>27</td>\n",
       "      <td>22.0</td>\n",
       "      <td>7.908417e+09</td>\n",
       "      <td>1.048444e+10</td>\n",
       "      <td>22.791193</td>\n",
       "      <td>23.073159</td>\n",
       "      <td>-0.026715</td>\n",
       "      <td>0.001241</td>\n",
       "      <td>-0.027956</td>\n",
       "      <td>0.103358</td>\n",
       "      <td>1</td>\n",
       "      <td>0.059760</td>\n",
       "      <td>0.051910</td>\n",
       "      <td>-0.044384</td>\n",
       "      <td>-0.011665</td>\n",
       "      <td>0.001407</td>\n",
       "      <td>0.010007</td>\n",
       "      <td>0.017726</td>\n",
       "      <td>0.025517</td>\n",
       "      <td>0.034661</td>\n",
       "      <td>0.047224</td>\n",
       "      <td>0.070970</td>\n",
       "      <td>P9</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>616139 rows × 26 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "         Stkcd      month  price  Rank  Freq  floatingvalue    totalvalue  \\\n",
       "34      000001 1994-03-31  15.05    36  23.0   2.184334e+09  4.054739e+09   \n",
       "35      000001 1994-04-30  15.99    37  21.0   2.320765e+09  4.307992e+09   \n",
       "36      000001 1994-05-31  14.60    38  21.0   2.119022e+09  3.933501e+09   \n",
       "37      000001 1994-06-30  13.44    39  22.0   2.407403e+09  3.620977e+09   \n",
       "38      000001 1994-07-31   8.00    40  18.0   2.292765e+09  3.448549e+09   \n",
       "...        ...        ...    ...   ...   ...            ...           ...   \n",
       "709877  605599 2023-07-31  13.92    23  21.0   8.166555e+09  1.082667e+10   \n",
       "709878  605599 2023-08-31  13.56    24  23.0   7.955351e+09  1.054667e+10   \n",
       "709879  605599 2023-09-30  14.54    25  20.0   8.530295e+09  1.130889e+10   \n",
       "709880  605599 2023-10-31  13.85    26  17.0   8.125488e+09  1.077222e+10   \n",
       "709881  605599 2023-11-30  13.48    27  22.0   7.908417e+09  1.048444e+10   \n",
       "\n",
       "            sizef      sizet    Return   rfmonth       ret  next_ret  w  \\\n",
       "34      21.504577  22.123152 -0.170799  0.008719 -0.179518  0.053739  1   \n",
       "35      21.565163  22.183738  0.062458  0.008719  0.053739 -0.095648  1   \n",
       "36      21.474221  22.092796 -0.086929  0.008719 -0.095648 -0.088171  1   \n",
       "37      21.601814  22.010010 -0.079452  0.008719 -0.088171 -0.056046  1   \n",
       "38      21.553024  21.961219 -0.047327  0.008719 -0.056046  0.553781  1   \n",
       "...           ...        ...       ...       ...       ...       ... ..   \n",
       "709877  22.823313  23.105278  0.053747  0.001241  0.052506 -0.027103  1   \n",
       "709878  22.797111  23.079076 -0.025862  0.001241 -0.027103  0.071030  1   \n",
       "709879  22.866890  23.148855  0.072271  0.001241  0.071030 -0.048696  1   \n",
       "709880  22.818272  23.100237 -0.047455  0.001241 -0.048696 -0.027956  1   \n",
       "709881  22.791193  23.073159 -0.026715  0.001241 -0.027956  0.103358  1   \n",
       "\n",
       "              ep  ep_recent       one       two     three      four      five  \\\n",
       "34      0.067405   0.067405  0.001488  0.002004  0.007389  0.013628  0.015989   \n",
       "35      0.063443   0.063443  0.002280  0.013236  0.019516  0.027554  0.041036   \n",
       "36      0.069483   0.069483  0.002379  0.015358  0.024298  0.037559  0.051864   \n",
       "37      0.075480   0.075480  0.002832  0.018418  0.027670  0.049931  0.061135   \n",
       "38      0.079254   0.079254  0.004204  0.027413  0.035091  0.061044  0.075252   \n",
       "...          ...        ...       ...       ...       ...       ...       ...   \n",
       "709877  0.041298   0.019832 -0.046221 -0.010509  0.003185  0.011029  0.018120   \n",
       "709878  0.054878   0.036802 -0.049601 -0.011916  0.002636  0.011005  0.018754   \n",
       "709879  0.051179   0.034322 -0.048772 -0.012110  0.002575  0.010991  0.018855   \n",
       "709880  0.058164   0.050524 -0.045980 -0.012401  0.001387  0.010373  0.018743   \n",
       "709881  0.059760   0.051910 -0.044384 -0.011665  0.001407  0.010007  0.017726   \n",
       "\n",
       "             six     seven     eight      nine  sort  \n",
       "34      0.021007  0.026544  0.042954  0.064559  Pmax  \n",
       "35      0.052489  0.062144  0.078678  0.084647    P8  \n",
       "36      0.059018  0.069656  0.076781  0.089289    P7  \n",
       "37      0.074077  0.086381  0.090049  0.114688    P7  \n",
       "38      0.087968  0.101297  0.123165  0.142412    P6  \n",
       "...          ...       ...       ...       ...   ...  \n",
       "709877  0.025115  0.033761  0.044528  0.069779    P8  \n",
       "709878  0.026098  0.034812  0.047238  0.071377    P9  \n",
       "709879  0.026206  0.034760  0.047755  0.071173    P9  \n",
       "709880  0.026326  0.035554  0.048309  0.071581    P9  \n",
       "709881  0.025517  0.034661  0.047224  0.070970    P9  \n",
       "\n",
       "[616139 rows x 26 columns]"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio = pd.merge(cross,fenweishu,on='month')\n",
    "portfolio['sort'] = np.where(\n",
    "    portfolio['ep'] <= portfolio['one'], 'P1',\n",
    "    np.where(\n",
    "        portfolio['ep'] <= portfolio['two'], 'P2',\n",
    "        np.where(\n",
    "            portfolio['ep'] <= portfolio['three'], 'P3',\n",
    "            np.where(\n",
    "                portfolio['ep'] <= portfolio['four'], 'P4',\n",
    "                np.where(\n",
    "                    portfolio['ep'] <= portfolio['five'], 'P5',\n",
    "                    np.where(\n",
    "                        portfolio['ep'] <= portfolio['six'], 'P6',\n",
    "                        np.where(\n",
    "                            portfolio['ep'] <= portfolio['seven'], 'P7',\n",
    "                            np.where(\n",
    "                                portfolio['ep'] <= portfolio['eight'], 'P8',\n",
    "                                np.where(\n",
    "                                    portfolio['ep'] <= portfolio['nine'],\n",
    "                                    'P9', 'Pmax')))))))))\n",
    "portfolio = portfolio.dropna(subset=['floatingvalue','next_ret','ep'])\n",
    "portfolio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>month</th>\n",
       "      <th>sort</th>\n",
       "      <th>p</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P1</td>\n",
       "      <td>0.038284</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P3</td>\n",
       "      <td>0.081305</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P5</td>\n",
       "      <td>-0.002070</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>P8</td>\n",
       "      <td>0.010496</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1991-02-28</td>\n",
       "      <td>Pmax</td>\n",
       "      <td>-0.041567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P6</td>\n",
       "      <td>-0.026517</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P7</td>\n",
       "      <td>-0.027443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P8</td>\n",
       "      <td>-0.019152</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>P9</td>\n",
       "      <td>-0.021802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>2023-12-31</td>\n",
       "      <td>Pmax</td>\n",
       "      <td>-0.005635</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3897 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          month  sort         p\n",
       "0    1991-02-28    P1  0.038284\n",
       "1    1991-02-28    P3  0.081305\n",
       "2    1991-02-28    P5 -0.002070\n",
       "3    1991-02-28    P8  0.010496\n",
       "4    1991-02-28  Pmax -0.041567\n",
       "...         ...   ...       ...\n",
       "3892 2023-12-31    P6 -0.026517\n",
       "3893 2023-12-31    P7 -0.027443\n",
       "3894 2023-12-31    P8 -0.019152\n",
       "3895 2023-12-31    P9 -0.021802\n",
       "3896 2023-12-31  Pmax -0.005635\n",
       "\n",
       "[3897 rows x 3 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 构造新的投资组合\n",
    "portfolio_value =  pd.DataFrame(\n",
    "    portfolio.groupby(['month','sort']).apply(lambda x: np.average(x['next_ret'],weights = x['totalvalue']),include_groups=False))#用每个月分组计算总市值加权的下个月的收益率\n",
    "portfolio_value = portfolio_value.reset_index()# 去索引\n",
    "portfolio_value.columns = ['month', 'sort', 'p']# 命名\n",
    "portfolio_value['month'] = portfolio_value['month'] + MonthEnd(1)# 月份加一\n",
    "portfolio_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>sort</th>\n",
       "      <th>P1</th>\n",
       "      <th>P2</th>\n",
       "      <th>P3</th>\n",
       "      <th>P4</th>\n",
       "      <th>P5</th>\n",
       "      <th>P6</th>\n",
       "      <th>P7</th>\n",
       "      <th>P8</th>\n",
       "      <th>P9</th>\n",
       "      <th>Pmax</th>\n",
       "      <th>My_portfolio</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>month</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1991-02-28</th>\n",
       "      <td>0.038284</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.081305</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.002070</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.010496</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.041567</td>\n",
       "      <td>-0.079851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-03-31</th>\n",
       "      <td>-0.044343</td>\n",
       "      <td>-0.070455</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.023904</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.059149</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.125264</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.069140</td>\n",
       "      <td>-0.024797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-04-30</th>\n",
       "      <td>-0.133193</td>\n",
       "      <td>0.120035</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.070484</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.097744</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.077512</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.000595</td>\n",
       "      <td>0.132598</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-05-31</th>\n",
       "      <td>0.238572</td>\n",
       "      <td>-0.006657</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.055289</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.130814</td>\n",
       "      <td>NaN</td>\n",
       "      <td>-0.031989</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.080639</td>\n",
       "      <td>-0.157933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1991-06-30</th>\n",
       "      <td>0.201980</td>\n",
       "      <td>0.177858</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.213185</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.184748</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.190006</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.190283</td>\n",
       "      <td>-0.011697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-08-31</th>\n",
       "      <td>-0.070702</td>\n",
       "      <td>-0.065108</td>\n",
       "      <td>-0.060387</td>\n",
       "      <td>-0.055580</td>\n",
       "      <td>-0.068235</td>\n",
       "      <td>-0.064091</td>\n",
       "      <td>-0.049394</td>\n",
       "      <td>-0.047246</td>\n",
       "      <td>-0.061972</td>\n",
       "      <td>-0.055716</td>\n",
       "      <td>0.014987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-09-30</th>\n",
       "      <td>0.003080</td>\n",
       "      <td>-0.009102</td>\n",
       "      <td>-0.019496</td>\n",
       "      <td>-0.017241</td>\n",
       "      <td>-0.009093</td>\n",
       "      <td>-0.013139</td>\n",
       "      <td>-0.021069</td>\n",
       "      <td>-0.035999</td>\n",
       "      <td>-0.012402</td>\n",
       "      <td>0.017093</td>\n",
       "      <td>0.014013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-10-31</th>\n",
       "      <td>0.026671</td>\n",
       "      <td>0.002212</td>\n",
       "      <td>-0.015104</td>\n",
       "      <td>0.003193</td>\n",
       "      <td>-0.020385</td>\n",
       "      <td>-0.034684</td>\n",
       "      <td>-0.026963</td>\n",
       "      <td>-0.022923</td>\n",
       "      <td>-0.032570</td>\n",
       "      <td>-0.044410</td>\n",
       "      <td>-0.071081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-11-30</th>\n",
       "      <td>0.009157</td>\n",
       "      <td>0.025058</td>\n",
       "      <td>0.021789</td>\n",
       "      <td>0.019388</td>\n",
       "      <td>0.017492</td>\n",
       "      <td>0.002561</td>\n",
       "      <td>0.026165</td>\n",
       "      <td>-0.013261</td>\n",
       "      <td>-0.011703</td>\n",
       "      <td>-0.012825</td>\n",
       "      <td>-0.021982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-31</th>\n",
       "      <td>-0.040710</td>\n",
       "      <td>-0.027280</td>\n",
       "      <td>-0.025472</td>\n",
       "      <td>-0.038377</td>\n",
       "      <td>-0.031421</td>\n",
       "      <td>-0.026517</td>\n",
       "      <td>-0.027443</td>\n",
       "      <td>-0.019152</td>\n",
       "      <td>-0.021802</td>\n",
       "      <td>-0.005635</td>\n",
       "      <td>0.035076</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>395 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "sort              P1        P2        P3        P4        P5        P6  \\\n",
       "month                                                                    \n",
       "1991-02-28  0.038284       NaN  0.081305       NaN -0.002070       NaN   \n",
       "1991-03-31 -0.044343 -0.070455       NaN  0.023904       NaN -0.059149   \n",
       "1991-04-30 -0.133193  0.120035       NaN  0.070484       NaN -0.097744   \n",
       "1991-05-31  0.238572 -0.006657       NaN  0.055289       NaN -0.130814   \n",
       "1991-06-30  0.201980  0.177858       NaN  0.213185       NaN  0.184748   \n",
       "...              ...       ...       ...       ...       ...       ...   \n",
       "2023-08-31 -0.070702 -0.065108 -0.060387 -0.055580 -0.068235 -0.064091   \n",
       "2023-09-30  0.003080 -0.009102 -0.019496 -0.017241 -0.009093 -0.013139   \n",
       "2023-10-31  0.026671  0.002212 -0.015104  0.003193 -0.020385 -0.034684   \n",
       "2023-11-30  0.009157  0.025058  0.021789  0.019388  0.017492  0.002561   \n",
       "2023-12-31 -0.040710 -0.027280 -0.025472 -0.038377 -0.031421 -0.026517   \n",
       "\n",
       "sort              P7        P8        P9      Pmax  My_portfolio  \n",
       "month                                                             \n",
       "1991-02-28       NaN  0.010496       NaN -0.041567     -0.079851  \n",
       "1991-03-31       NaN -0.125264       NaN -0.069140     -0.024797  \n",
       "1991-04-30       NaN -0.077512       NaN -0.000595      0.132598  \n",
       "1991-05-31       NaN -0.031989       NaN  0.080639     -0.157933  \n",
       "1991-06-30       NaN  0.190006       NaN  0.190283     -0.011697  \n",
       "...              ...       ...       ...       ...           ...  \n",
       "2023-08-31 -0.049394 -0.047246 -0.061972 -0.055716      0.014987  \n",
       "2023-09-30 -0.021069 -0.035999 -0.012402  0.017093      0.014013  \n",
       "2023-10-31 -0.026963 -0.022923 -0.032570 -0.044410     -0.071081  \n",
       "2023-11-30  0.026165 -0.013261 -0.011703 -0.012825     -0.021982  \n",
       "2023-12-31 -0.027443 -0.019152 -0.021802 -0.005635      0.035076  \n",
       "\n",
       "[395 rows x 11 columns]"
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "portfolio_value = portfolio_value.pivot_table(index='month',\n",
    "                                                    columns='sort',\n",
    "                                                    values='p')\n",
    "portfolio_value['My_portfolio'] = portfolio_value['Pmax'] - portfolio_value['P1']# 买最大的价值股，卖最小的成长股，不同于规模策略\n",
    "portfolio_value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "                            OLS Regression Results                            \n",
      "==============================================================================\n",
      "Dep. Variable:           My_portfolio   R-squared:                       0.000\n",
      "Model:                            OLS   Adj. R-squared:                  0.000\n",
      "Method:                 Least Squares   F-statistic:                       nan\n",
      "Date:                Wed, 11 Dec 2024   Prob (F-statistic):                nan\n",
      "Time:                        16:24:31   Log-Likelihood:                 380.88\n",
      "No. Observations:                 288   AIC:                            -759.8\n",
      "Df Residuals:                     287   BIC:                            -756.1\n",
      "Df Model:                           0                                         \n",
      "Covariance Type:                  HAC                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "Intercept      0.0054      0.003      1.713      0.087      -0.001       0.011\n",
      "==============================================================================\n",
      "Omnibus:                       19.099   Durbin-Watson:                   1.914\n",
      "Prob(Omnibus):                  0.000   Jarque-Bera (JB):               43.292\n",
      "Skew:                           0.289   Prob(JB):                     3.98e-10\n",
      "Kurtosis:                       4.809   Cond. No.                         1.00\n",
      "==============================================================================\n",
      "\n",
      "Notes:\n",
      "[1] Standard Errors are heteroscedasticity and autocorrelation robust (HAC) using 6 lags and without small sample correction\n"
     ]
    }
   ],
   "source": [
    "# 回归到1上\n",
    "model_value = smf.ols('My_portfolio ~ 1',data=portfolio_value['2000':'2023']).fit(\n",
    "    cov_type='HAC', cov_kwds={'maxlags': 6})\n",
    "print(model_value.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "相比规模效应收益率弱很多，而且在95%、99%置信水平上都不显著，只在90%置信水平下显著"
   ]
  }
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